vllm - 💡(How to fix) Fix [Bug]:TimeoutError: RPC call to sample_tokens timed out. when pp is on under xpu env [1 participants]
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vllm-project/vllm#38976•Fetched 2026-04-08 02:44:37
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zwh20081Error Message
WARNING 04-04 18:12:14 [argparse_utils.py:191] With vllm serve, you should provide the model as a positional argument or in a config file instead of via the --model option. The --model option will be removed in v0.13.
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █ █ █▄ ▄█
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.19.1rc1.dev29+g93726b2a1
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █▄█▀ █ █ █ █ model /data/models/gpt-oss-20b/
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:233] non-default args: {'model_tag': '/data/models/gpt-oss-20b/', 'host': '0.0.0.0', 'model': '/data/models/gpt-oss-20b/', 'trust_remote_code': True, 'max_model_len': 8192, 'enforce_eager': True, 'disable_sliding_window': True, 'distributed_executor_backend': 'mp', 'pipeline_parallel_size': 2, 'tensor_parallel_size': 2, 'block_size': 64, 'gpu_memory_utilization': 0.87, 'max_num_batched_tokens': 8192}
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:554] Resolved architecture: GptOssForCausalLM
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:1685] Using max model len 8192
(APIServer pid=335596) INFO 04-04 18:12:14 [scheduler.py:238] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=335596) INFO 04-04 18:12:14 [config.py:126] Overriding max cuda graph capture size to 1024 for performance.
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:799] Asynchronous scheduling is enabled.
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(APIServer pid=335596) INFO 04-04 18:12:14 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:1046] Cudagraph is disabled under eager mode
(APIServer pid=335596) WARNING 04-04 18:12:14 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(APIServer pid=335596) INFO 04-04 18:12:14 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(EngineCore pid=336188) INFO 04-04 18:12:19 [core.py:105] Initializing a V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto')
(EngineCore pid=336188) INFO 04-04 18:12:19 [multiproc_executor.py:137] DP group leader: node_rank=0, node_rank_within_dp=0, master_addr=127.0.0.1, mq_connect_ip=192.168.5.175 (local), world_size=4, local_world_size=4
(Worker pid=336700) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=3 local_rank=3 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336699) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=2 local_rank=2 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=0 local_rank=0 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336698) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=1 local_rank=1 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:25 [parallel_state.py:1712] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
2026:04:04-18:12:25:336697 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336697 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336698 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336698 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336700 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336700 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336699 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336699 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:26:336698:[1] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336699:[2] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336697:[0] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336700:[3] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:26 [gpu_model_runner.py:4735] Starting to load model /data/models/gpt-oss-20b/...
(Worker_PP0_TP1 pid=336698) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:81] Using Flash Attention backend.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [flash_attn.py:622] Using FlashAttention version 2
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [mxfp4.py:352] Using 'XPU' Mxfp4 MoE backend.
(Worker_PP1_TP0 pid=336699) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP1_TP1 pid=336700) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
Loading safetensors checkpoint shards: 0% Completed | 0/3 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 33% Completed | 1/3 [00:00<00:00, 2.23it/s]
Loading safetensors checkpoint shards: 67% Completed | 2/3 [00:00<00:00, 2.29it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.64it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.77it/s]
(Worker_PP0_TP0 pid=336697)
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [default_loader.py:384] Loading weights took 1.75 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [mxfp4.py:836] Using MoEPrepareAndFinalizeNoDPEPModular
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [gpu_model_runner.py:4820] Model loading took 3.85 GiB memory and 2.185793 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [gpu_worker.py:436] Available KV cache memory: 14.86 GiB
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1319] GPU KV cache size: 1,222,720 tokens
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1324] Maximum concurrency for 8,192 tokens per request: 149.26x
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [utils.py:60] _KV_CACHE_LAYOUT_OVERRIDE variable detected. Setting KV cache layout to NHD.
(EngineCore pid=336188) INFO 04-04 18:12:32 [core.py:283] init engine (profile, create kv cache, warmup model) took 3.13 seconds
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:799] Asynchronous scheduling is enabled.
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(EngineCore pid=336188) INFO 04-04 18:12:33 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:1046] Cudagraph is disabled under eager mode
(EngineCore pid=336188) WARNING 04-04 18:12:33 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(EngineCore pid=336188) INFO 04-04 18:12:33 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(APIServer pid=335596) INFO 04-04 18:12:33 [api_server.py:604] Supported tasks: ['generate']
(APIServer pid=335596) WARNING 04-04 18:12:33 [serving.py:233] For gpt-oss, we ignore --enable-auto-tool-choice and always enable tool use.
(APIServer pid=335596) INFO 04-04 18:12:34 [hf.py:314] Detected the chat template content format to be 'string'. You can set --chat-template-content-format to override this.
(APIServer pid=335596) INFO 04-04 18:12:34 [api_server.py:608] Starting vLLM server on http://0.0.0.0:8000
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:37] Available routes are:
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /tokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /detokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /load, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /version, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /health, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /metrics, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/models, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /invocations, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /generative_scoring, Methods: POST
(APIServer pid=335596) INFO: Started server process [335596]
(APIServer pid=335596) INFO: Waiting for application startup.
(APIServer pid=335596) INFO: Application startup complete.
(APIServer pid=335596) INFO: 127.0.0.1:34608 - "GET /metrics HTTP/1.1" 200 OK
(APIServer pid=335596) INFO: 127.0.0.1:34610 - "POST /v1/completions HTTP/1.1" 200 OK
(Worker_PP0_TP0 pid=336697) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP0 pid=336697) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(Worker_PP0_TP1 pid=336698) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP1 pid=336698) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(APIServer pid=335596) INFO 04-04 18:13:04 [loggers.py:259] Engine 000: Avg prompt throughput: 102.4 tokens/s, Avg generation throughput: 0.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(APIServer pid=335596) INFO 04-04 18:13:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(EngineCore pid=336188) INFO 04-04 18:13:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:14:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:15:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:16:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:72] Dumping input data for V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto'),
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:79] Dumping scheduler output for model execution: SchedulerOutput(scheduled_new_reqs=[], scheduled_cached_reqs=CachedRequestData(req_ids=['cmpl-bench-dd7f173a-0-0-8a43c102'],resumed_req_ids=set(),new_token_ids_lens=[],all_token_ids_lens={},new_block_ids=[([17],)],num_computed_tokens=[1024],num_output_tokens=[1]), num_scheduled_tokens={cmpl-bench-dd7f173a-0-0-8a43c102: 1}, total_num_scheduled_tokens=1, scheduled_spec_decode_tokens={}, scheduled_encoder_inputs={}, num_common_prefix_blocks=[17], finished_req_ids=[], free_encoder_mm_hashes=[], preempted_req_ids=[], has_structured_output_requests=false, pending_structured_output_tokens=false, num_invalid_spec_tokens=null, kv_connector_metadata=null, ec_connector_metadata=null, new_block_ids_to_zero=null)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:81] Dumping scheduler stats: SchedulerStats(num_running_reqs=1, num_waiting_reqs=0, step_counter=0, current_wave=0, kv_cache_usage=0.0008898659966498634, encoder_cache_usage=0.0, prefix_cache_stats=PrefixCacheStats(reset=False, requests=0, queries=0, hits=0, preempted_requests=0, preempted_queries=0, preempted_hits=0), connector_prefix_cache_stats=None, kv_cache_eviction_events=[], spec_decoding_stats=None, kv_connector_stats=None, waiting_lora_adapters={}, running_lora_adapters={}, cudagraph_stats=None, perf_stats=None)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] EngineCore encountered a fatal error.
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 394, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] status, result = mq.dequeue(timeout=dequeue_timeout)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 755, in dequeue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] with self.acquire_read(timeout, indefinite) as buf:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/contextlib.py", line 137, in enter
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return next(self.gen)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 674, in acquire_read
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._spin_condition.wait(timeout_ms=read_timeout.timeout_ms())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 631, in timeout_ms
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] The above exception was the direct cause of the following exception:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1101, in run_engine_core
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] engine_core.run_busy_loop()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1142, in run_busy_loop
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._process_engine_step()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1181, in _process_engine_step
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] outputs, model_executed = self.step_fn()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 499, in step_with_batch_queue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] model_output = future.result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 88, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return super().result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 449, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return self.__get_result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise self._exception
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 92, in _wait_for_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] response = self.aggregate(self.get_response())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 396, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError(f"RPC call to {method} timed out.") from e
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError: RPC call to sample_tokens timed out.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] AsyncLLM output_handler failed.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] Traceback (most recent call last):
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/async_llm.py", line 663, in output_handler
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] outputs = await engine_core.get_output_async()
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/core_client.py", line 970, in get_output_async
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] raise self._format_exception(outputs) from None
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] vllm.v1.engine.exceptions.EngineDeadError: EngineCore encountered an issue. See stack trace (above) for the root cause.
(APIServer pid=335596) INFO: Shutting down
(APIServer pid=335596) INFO: Waiting for application shutdown.
(APIServer pid=335596) INFO: Application shutdown complete.
(APIServer pid=335596) INFO: Finished server process [335596]
Root Cause
WARNING 04-04 18:12:14 [argparse_utils.py:191] With `vllm serve`, you should provide the model as a positional argument or in a config file instead of via the `--model` option. The `--model` option will be removed in v0.13.
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █ █ █▄ ▄█
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.19.1rc1.dev29+g93726b2a1
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █▄█▀ █ █ █ █ model /data/models/gpt-oss-20b/
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:233] non-default args: {'model_tag': '/data/models/gpt-oss-20b/', 'host': '0.0.0.0', 'model': '/data/models/gpt-oss-20b/', 'trust_remote_code': True, 'max_model_len': 8192, 'enforce_eager': True, 'disable_sliding_window': True, 'distributed_executor_backend': 'mp', 'pipeline_parallel_size': 2, 'tensor_parallel_size': 2, 'block_size': 64, 'gpu_memory_utilization': 0.87, 'max_num_batched_tokens': 8192}
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:554] Resolved architecture: GptOssForCausalLM
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:1685] Using max model len 8192
(APIServer pid=335596) INFO 04-04 18:12:14 [scheduler.py:238] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=335596) INFO 04-04 18:12:14 [config.py:126] Overriding max cuda graph capture size to 1024 for performance.
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:799] Asynchronous scheduling is enabled.
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(APIServer pid=335596) INFO 04-04 18:12:14 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:1046] Cudagraph is disabled under eager mode
(APIServer pid=335596) WARNING 04-04 18:12:14 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(APIServer pid=335596) INFO 04-04 18:12:14 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(EngineCore pid=336188) INFO 04-04 18:12:19 [core.py:105] Initializing a V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto')
(EngineCore pid=336188) INFO 04-04 18:12:19 [multiproc_executor.py:137] DP group leader: node_rank=0, node_rank_within_dp=0, master_addr=127.0.0.1, mq_connect_ip=192.168.5.175 (local), world_size=4, local_world_size=4
(Worker pid=336700) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=3 local_rank=3 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336699) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=2 local_rank=2 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=0 local_rank=0 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336698) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=1 local_rank=1 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:25 [parallel_state.py:1712] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
2026:04:04-18:12:25:336697 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336697 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336698 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336698 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336700 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336700 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336699 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336699 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:26:336698:[1] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336699:[2] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336697:[0] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336700:[3] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:26 [gpu_model_runner.py:4735] Starting to load model /data/models/gpt-oss-20b/...
(Worker_PP0_TP1 pid=336698) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:81] Using Flash Attention backend.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [flash_attn.py:622] Using FlashAttention version 2
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [mxfp4.py:352] Using 'XPU' Mxfp4 MoE backend.
(Worker_PP1_TP0 pid=336699) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP1_TP1 pid=336700) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
Loading safetensors checkpoint shards: 0% Completed | 0/3 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 33% Completed | 1/3 [00:00<00:00, 2.23it/s]
Loading safetensors checkpoint shards: 67% Completed | 2/3 [00:00<00:00, 2.29it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.64it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.77it/s]
(Worker_PP0_TP0 pid=336697)
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [default_loader.py:384] Loading weights took 1.75 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [mxfp4.py:836] Using MoEPrepareAndFinalizeNoDPEPModular
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [gpu_model_runner.py:4820] Model loading took 3.85 GiB memory and 2.185793 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [gpu_worker.py:436] Available KV cache memory: 14.86 GiB
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1319] GPU KV cache size: 1,222,720 tokens
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1324] Maximum concurrency for 8,192 tokens per request: 149.26x
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [utils.py:60] `_KV_CACHE_LAYOUT_OVERRIDE` variable detected. Setting KV cache layout to NHD.
(EngineCore pid=336188) INFO 04-04 18:12:32 [core.py:283] init engine (profile, create kv cache, warmup model) took 3.13 seconds
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:799] Asynchronous scheduling is enabled.
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(EngineCore pid=336188) INFO 04-04 18:12:33 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:1046] Cudagraph is disabled under eager mode
(EngineCore pid=336188) WARNING 04-04 18:12:33 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(EngineCore pid=336188) INFO 04-04 18:12:33 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(APIServer pid=335596) INFO 04-04 18:12:33 [api_server.py:604] Supported tasks: ['generate']
(APIServer pid=335596) WARNING 04-04 18:12:33 [serving.py:233] For gpt-oss, we ignore --enable-auto-tool-choice and always enable tool use.
(APIServer pid=335596) INFO 04-04 18:12:34 [hf.py:314] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this.
(APIServer pid=335596) INFO 04-04 18:12:34 [api_server.py:608] Starting vLLM server on http://0.0.0.0:8000
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:37] Available routes are:
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /tokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /detokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /load, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /version, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /health, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /metrics, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/models, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /invocations, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /generative_scoring, Methods: POST
(APIServer pid=335596) INFO: Started server process [335596]
(APIServer pid=335596) INFO: Waiting for application startup.
(APIServer pid=335596) INFO: Application startup complete.
(APIServer pid=335596) INFO: 127.0.0.1:34608 - "GET /metrics HTTP/1.1" 200 OK
(APIServer pid=335596) INFO: 127.0.0.1:34610 - "POST /v1/completions HTTP/1.1" 200 OK
(Worker_PP0_TP0 pid=336697) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP0 pid=336697) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(Worker_PP0_TP1 pid=336698) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP1 pid=336698) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(APIServer pid=335596) INFO 04-04 18:13:04 [loggers.py:259] Engine 000: Avg prompt throughput: 102.4 tokens/s, Avg generation throughput: 0.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(APIServer pid=335596) INFO 04-04 18:13:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(EngineCore pid=336188) INFO 04-04 18:13:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:14:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:15:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:16:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:72] Dumping input data for V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto'),
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:79] Dumping scheduler output for model execution: SchedulerOutput(scheduled_new_reqs=[], scheduled_cached_reqs=CachedRequestData(req_ids=['cmpl-bench-dd7f173a-0-0-8a43c102'],resumed_req_ids=set(),new_token_ids_lens=[],all_token_ids_lens={},new_block_ids=[([17],)],num_computed_tokens=[1024],num_output_tokens=[1]), num_scheduled_tokens={cmpl-bench-dd7f173a-0-0-8a43c102: 1}, total_num_scheduled_tokens=1, scheduled_spec_decode_tokens={}, scheduled_encoder_inputs={}, num_common_prefix_blocks=[17], finished_req_ids=[], free_encoder_mm_hashes=[], preempted_req_ids=[], has_structured_output_requests=false, pending_structured_output_tokens=false, num_invalid_spec_tokens=null, kv_connector_metadata=null, ec_connector_metadata=null, new_block_ids_to_zero=null)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:81] Dumping scheduler stats: SchedulerStats(num_running_reqs=1, num_waiting_reqs=0, step_counter=0, current_wave=0, kv_cache_usage=0.0008898659966498634, encoder_cache_usage=0.0, prefix_cache_stats=PrefixCacheStats(reset=False, requests=0, queries=0, hits=0, preempted_requests=0, preempted_queries=0, preempted_hits=0), connector_prefix_cache_stats=None, kv_cache_eviction_events=[], spec_decoding_stats=None, kv_connector_stats=None, waiting_lora_adapters={}, running_lora_adapters={}, cudagraph_stats=None, perf_stats=None)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] EngineCore encountered a fatal error.
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 394, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] status, result = mq.dequeue(timeout=dequeue_timeout)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 755, in dequeue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] with self.acquire_read(timeout, indefinite) as buf:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/contextlib.py", line 137, in __enter__
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return next(self.gen)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 674, in acquire_read
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._spin_condition.wait(timeout_ms=read_timeout.timeout_ms())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 631, in timeout_ms
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] The above exception was the direct cause of the following exception:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1101, in run_engine_core
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] engine_core.run_busy_loop()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1142, in run_busy_loop
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._process_engine_step()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1181, in _process_engine_step
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] outputs, model_executed = self.step_fn()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 499, in step_with_batch_queue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] model_output = future.result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 88, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return super().result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 449, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return self.__get_result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise self._exception
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 92, in _wait_for_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] response = self.aggregate(self.get_response())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 396, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError(f"RPC call to {method} timed out.") from e
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError: RPC call to sample_tokens timed out.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] AsyncLLM output_handler failed.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] Traceback (most recent call last):
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/async_llm.py", line 663, in output_handler
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] outputs = await engine_core.get_output_async()
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/core_client.py", line 970, in get_output_async
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] raise self._format_exception(outputs) from None
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] vllm.v1.engine.exceptions.EngineDeadError: EngineCore encountered an issue. See stack trace (above) for the root cause.
(APIServer pid=335596) INFO: Shutting down
(APIServer pid=335596) INFO: Waiting for application shutdown.
(APIServer pid=335596) INFO: Application shutdown complete.
(APIServer pid=335596) INFO: Finished server process [335596]Fix Action
Fix / Workaround
============================== CPU Info
Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 48 On-line CPU(s) list: 0-47 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) w7-3455 CPU family: 6 Model: 143 Thread(s) per core: 2 Core(s) per socket: 24 Socket(s): 1 Stepping: 5 CPU(s) scaling MHz: 25% CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 1.1 MiB (24 instances) L1i cache: 768 KiB (24 instances) L2 cache: 48 MiB (24 instances) L3 cache: 67.5 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-47 Vulnerability Gather data sampling: Not affected Vulnerability Ghostwrite: Not affected Vulnerability Indirect target selection: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Old microcode: Vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsa: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
Code Example
Collecting environment information...
==============================
System Info
==============================
OS : Ubuntu 25.10 (x86_64)
GCC version : (Ubuntu 15.2.0-4ubuntu4) 15.2.0
Clang version : Could not collect
CMake version : version 4.3.1
Libc version : glibc-2.42
==============================
PyTorch Info
==============================
PyTorch version : 2.11.0+xpu
Is debug build : False
CUDA used to build PyTorch : None
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] (64-bit runtime)
Python platform : Linux-6.17.0-20-generic-x86_64-with-glibc2.42
==============================
CUDA / GPU Info
==============================
Is CUDA available : False
CUDA runtime version : No CUDA
CUDA_MODULE_LOADING set to : N/A
GPU models and configuration : No CUDA
Nvidia driver version : No CUDA
cuDNN version : No CUDA
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 48
On-line CPU(s) list: 0-47
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) w7-3455
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 1
Stepping: 5
CPU(s) scaling MHz: 25%
CPU max MHz: 4800.0000
CPU min MHz: 800.0000
BogoMIPS: 4992.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 1.1 MiB (24 instances)
L1i cache: 768 KiB (24 instances)
L2 cache: 48 MiB (24 instances)
L3 cache: 67.5 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-47
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Old microcode: Vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
==============================
Versions of relevant libraries
==============================
[pip3] numpy==2.4.3
[pip3] pyzmq==27.1.0
[pip3] torch==2.11.0+xpu
[pip3] torchao==0.17.0+xpu
[pip3] torchaudio==2.11.0+xpu
[pip3] torchvision==0.26.0+xpu
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[pip3] triton-xpu==3.7.0
[conda] mkl 2025.3.1 pypi_0 pypi
[conda] numpy 2.4.3 pypi_0 pypi
[conda] onemkl-license 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-blas 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-dft 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-lapack 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-rng 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-sparse 2025.3.1 pypi_0 pypi
[conda] pyzmq 27.1.0 pypi_0 pypi
[conda] torch 2.11.0+xpu pypi_0 pypi
[conda] torchao 0.17.0+xpu pypi_0 pypi
[conda] torchaudio 2.11.0+xpu pypi_0 pypi
[conda] torchvision 0.26.0+xpu pypi_0 pypi
[conda] transformers 4.57.6 pypi_0 pypi
[conda] triton 3.6.0 pypi_0 pypi
[conda] triton-xpu 3.7.0 pypi_0 pypi
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.19.1rc1.dev29+g93726b2a1 (git sha: 93726b2a1)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
Could not collect
==============================
Environment Variables
==============================
VLLM_ALLOW_LONG_MAX_MODEL_LEN=1
VLLM_WORKER_MULTIPROC_METHOD=spawn
VLLM_XPU_ENABLE_XPU_GRAPH=1
LD_LIBRARY_PATH=/opt/intel/oneapi/tcm/1.4/lib:/opt/intel/oneapi/umf/1.0/lib:/opt/intel/oneapi/tbb/2022.3/env/../lib/intel64/gcc4.8:/opt/intel/oneapi/mpi/2021.17/opt/mpi/libfabric/lib:/opt/intel/oneapi/mpi/2021.17/lib:/opt/intel/oneapi/mkl/2025.3/lib:/opt/intel/oneapi/ippcp/2025.3/lib/:/opt/intel/oneapi/ipp/2022.3/lib:/opt/intel/oneapi/dnnl/2025.3/lib:/opt/intel/oneapi/debugger/2025.3/opt/debugger/lib:/opt/intel/oneapi/dal/2025.10/lib:/opt/intel/oneapi/compiler/2025.3/opt/compiler/lib:/opt/intel/oneapi/compiler/2025.3/lib:/opt/intel/oneapi/ccl/2021.17/lib/:/home/cjai/miniforge3/envs/vllm/lib:/opt/intel/oneapi/tcm/1.4/lib:/opt/intel/oneapi/umf/1.0/lib:/opt/intel/oneapi/tbb/2022.3/env/../lib/intel64/gcc4.8:/opt/intel/oneapi/mpi/2021.17/opt/mpi/libfabric/lib:/opt/intel/oneapi/mpi/2021.17/lib:/opt/intel/oneapi/mkl/2025.3/lib:/opt/intel/oneapi/ippcp/2025.3/lib/:/opt/intel/oneapi/ipp/2022.3/lib:/opt/intel/oneapi/dnnl/2025.3/lib:/opt/intel/oneapi/debugger/2025.3/opt/debugger/lib:/opt/intel/oneapi/dal/2025.10/lib:/opt/intel/oneapi/compiler/2025.3/opt/compiler/lib:/opt/intel/oneapi/compiler/2025.3/lib:/opt/intel/oneapi/ccl/2021.17/lib/
OMP_NUM_THREADS=48
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_cjai
---
vllm serve --model /data/models/gpt-oss-20b/ --enforce-eager --port 8000 --host 0.0.0.0 --trust-remote-code --disable-sliding-window --gpu-memory-util=0.87 --max-num-batched-tokens=8192 --max-model-len=8192 --block-size 64 -tp=2 -pp 2 --distributed-executor-backend=mp
---
WARNING 04-04 18:12:14 [argparse_utils.py:191] With `vllm serve`, you should provide the model as a positional argument or in a config file instead of via the `--model` option. The `--model` option will be removed in v0.13.
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █ █ █▄ ▄█
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.19.1rc1.dev29+g93726b2a1
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █▄█▀ █ █ █ █ model /data/models/gpt-oss-20b/
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:233] non-default args: {'model_tag': '/data/models/gpt-oss-20b/', 'host': '0.0.0.0', 'model': '/data/models/gpt-oss-20b/', 'trust_remote_code': True, 'max_model_len': 8192, 'enforce_eager': True, 'disable_sliding_window': True, 'distributed_executor_backend': 'mp', 'pipeline_parallel_size': 2, 'tensor_parallel_size': 2, 'block_size': 64, 'gpu_memory_utilization': 0.87, 'max_num_batched_tokens': 8192}
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:554] Resolved architecture: GptOssForCausalLM
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:1685] Using max model len 8192
(APIServer pid=335596) INFO 04-04 18:12:14 [scheduler.py:238] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=335596) INFO 04-04 18:12:14 [config.py:126] Overriding max cuda graph capture size to 1024 for performance.
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:799] Asynchronous scheduling is enabled.
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(APIServer pid=335596) INFO 04-04 18:12:14 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:1046] Cudagraph is disabled under eager mode
(APIServer pid=335596) WARNING 04-04 18:12:14 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(APIServer pid=335596) INFO 04-04 18:12:14 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(EngineCore pid=336188) INFO 04-04 18:12:19 [core.py:105] Initializing a V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto')
(EngineCore pid=336188) INFO 04-04 18:12:19 [multiproc_executor.py:137] DP group leader: node_rank=0, node_rank_within_dp=0, master_addr=127.0.0.1, mq_connect_ip=192.168.5.175 (local), world_size=4, local_world_size=4
(Worker pid=336700) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=3 local_rank=3 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336699) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=2 local_rank=2 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=0 local_rank=0 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336698) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=1 local_rank=1 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:25 [parallel_state.py:1712] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
2026:04:04-18:12:25:336697 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336697 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336698 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336698 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336700 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336700 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336699 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336699 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:26:336698:[1] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336699:[2] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336697:[0] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336700:[3] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:26 [gpu_model_runner.py:4735] Starting to load model /data/models/gpt-oss-20b/...
(Worker_PP0_TP1 pid=336698) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:81] Using Flash Attention backend.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [flash_attn.py:622] Using FlashAttention version 2
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [mxfp4.py:352] Using 'XPU' Mxfp4 MoE backend.
(Worker_PP1_TP0 pid=336699) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP1_TP1 pid=336700) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
Loading safetensors checkpoint shards: 0% Completed | 0/3 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 33% Completed | 1/3 [00:00<00:00, 2.23it/s]
Loading safetensors checkpoint shards: 67% Completed | 2/3 [00:00<00:00, 2.29it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.64it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.77it/s]
(Worker_PP0_TP0 pid=336697)
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [default_loader.py:384] Loading weights took 1.75 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [mxfp4.py:836] Using MoEPrepareAndFinalizeNoDPEPModular
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [gpu_model_runner.py:4820] Model loading took 3.85 GiB memory and 2.185793 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [gpu_worker.py:436] Available KV cache memory: 14.86 GiB
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1319] GPU KV cache size: 1,222,720 tokens
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1324] Maximum concurrency for 8,192 tokens per request: 149.26x
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [utils.py:60] `_KV_CACHE_LAYOUT_OVERRIDE` variable detected. Setting KV cache layout to NHD.
(EngineCore pid=336188) INFO 04-04 18:12:32 [core.py:283] init engine (profile, create kv cache, warmup model) took 3.13 seconds
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:799] Asynchronous scheduling is enabled.
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(EngineCore pid=336188) INFO 04-04 18:12:33 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:1046] Cudagraph is disabled under eager mode
(EngineCore pid=336188) WARNING 04-04 18:12:33 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(EngineCore pid=336188) INFO 04-04 18:12:33 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(APIServer pid=335596) INFO 04-04 18:12:33 [api_server.py:604] Supported tasks: ['generate']
(APIServer pid=335596) WARNING 04-04 18:12:33 [serving.py:233] For gpt-oss, we ignore --enable-auto-tool-choice and always enable tool use.
(APIServer pid=335596) INFO 04-04 18:12:34 [hf.py:314] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this.
(APIServer pid=335596) INFO 04-04 18:12:34 [api_server.py:608] Starting vLLM server on http://0.0.0.0:8000
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:37] Available routes are:
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /tokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /detokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /load, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /version, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /health, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /metrics, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/models, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /invocations, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /generative_scoring, Methods: POST
(APIServer pid=335596) INFO: Started server process [335596]
(APIServer pid=335596) INFO: Waiting for application startup.
(APIServer pid=335596) INFO: Application startup complete.
(APIServer pid=335596) INFO: 127.0.0.1:34608 - "GET /metrics HTTP/1.1" 200 OK
(APIServer pid=335596) INFO: 127.0.0.1:34610 - "POST /v1/completions HTTP/1.1" 200 OK
(Worker_PP0_TP0 pid=336697) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP0 pid=336697) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(Worker_PP0_TP1 pid=336698) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP1 pid=336698) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(APIServer pid=335596) INFO 04-04 18:13:04 [loggers.py:259] Engine 000: Avg prompt throughput: 102.4 tokens/s, Avg generation throughput: 0.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(APIServer pid=335596) INFO 04-04 18:13:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(EngineCore pid=336188) INFO 04-04 18:13:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:14:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:15:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:16:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:72] Dumping input data for V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto'),
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:79] Dumping scheduler output for model execution: SchedulerOutput(scheduled_new_reqs=[], scheduled_cached_reqs=CachedRequestData(req_ids=['cmpl-bench-dd7f173a-0-0-8a43c102'],resumed_req_ids=set(),new_token_ids_lens=[],all_token_ids_lens={},new_block_ids=[([17],)],num_computed_tokens=[1024],num_output_tokens=[1]), num_scheduled_tokens={cmpl-bench-dd7f173a-0-0-8a43c102: 1}, total_num_scheduled_tokens=1, scheduled_spec_decode_tokens={}, scheduled_encoder_inputs={}, num_common_prefix_blocks=[17], finished_req_ids=[], free_encoder_mm_hashes=[], preempted_req_ids=[], has_structured_output_requests=false, pending_structured_output_tokens=false, num_invalid_spec_tokens=null, kv_connector_metadata=null, ec_connector_metadata=null, new_block_ids_to_zero=null)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:81] Dumping scheduler stats: SchedulerStats(num_running_reqs=1, num_waiting_reqs=0, step_counter=0, current_wave=0, kv_cache_usage=0.0008898659966498634, encoder_cache_usage=0.0, prefix_cache_stats=PrefixCacheStats(reset=False, requests=0, queries=0, hits=0, preempted_requests=0, preempted_queries=0, preempted_hits=0), connector_prefix_cache_stats=None, kv_cache_eviction_events=[], spec_decoding_stats=None, kv_connector_stats=None, waiting_lora_adapters={}, running_lora_adapters={}, cudagraph_stats=None, perf_stats=None)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] EngineCore encountered a fatal error.
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 394, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] status, result = mq.dequeue(timeout=dequeue_timeout)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 755, in dequeue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] with self.acquire_read(timeout, indefinite) as buf:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/contextlib.py", line 137, in __enter__
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return next(self.gen)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 674, in acquire_read
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._spin_condition.wait(timeout_ms=read_timeout.timeout_ms())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 631, in timeout_ms
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] The above exception was the direct cause of the following exception:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1101, in run_engine_core
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] engine_core.run_busy_loop()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1142, in run_busy_loop
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._process_engine_step()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1181, in _process_engine_step
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] outputs, model_executed = self.step_fn()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 499, in step_with_batch_queue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] model_output = future.result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 88, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return super().result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 449, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return self.__get_result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise self._exception
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 92, in _wait_for_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] response = self.aggregate(self.get_response())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 396, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError(f"RPC call to {method} timed out.") from e
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError: RPC call to sample_tokens timed out.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] AsyncLLM output_handler failed.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] Traceback (most recent call last):
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/async_llm.py", line 663, in output_handler
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] outputs = await engine_core.get_output_async()
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/core_client.py", line 970, in get_output_async
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] raise self._format_exception(outputs) from None
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] vllm.v1.engine.exceptions.EngineDeadError: EngineCore encountered an issue. See stack trace (above) for the root cause.
(APIServer pid=335596) INFO: Shutting down
(APIServer pid=335596) INFO: Waiting for application shutdown.
(APIServer pid=335596) INFO: Application shutdown complete.
(APIServer pid=335596) INFO: Finished server process [335596]RAW_BUFFERClick to expand / collapse
Your current environment
<details> <summary>The output of <code>python collect_env.py</code></summary>Collecting environment information...
==============================
System Info
==============================
OS : Ubuntu 25.10 (x86_64)
GCC version : (Ubuntu 15.2.0-4ubuntu4) 15.2.0
Clang version : Could not collect
CMake version : version 4.3.1
Libc version : glibc-2.42
==============================
PyTorch Info
==============================
PyTorch version : 2.11.0+xpu
Is debug build : False
CUDA used to build PyTorch : None
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] (64-bit runtime)
Python platform : Linux-6.17.0-20-generic-x86_64-with-glibc2.42
==============================
CUDA / GPU Info
==============================
Is CUDA available : False
CUDA runtime version : No CUDA
CUDA_MODULE_LOADING set to : N/A
GPU models and configuration : No CUDA
Nvidia driver version : No CUDA
cuDNN version : No CUDA
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 48
On-line CPU(s) list: 0-47
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) w7-3455
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 1
Stepping: 5
CPU(s) scaling MHz: 25%
CPU max MHz: 4800.0000
CPU min MHz: 800.0000
BogoMIPS: 4992.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 1.1 MiB (24 instances)
L1i cache: 768 KiB (24 instances)
L2 cache: 48 MiB (24 instances)
L3 cache: 67.5 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-47
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Old microcode: Vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
==============================
Versions of relevant libraries
==============================
[pip3] numpy==2.4.3
[pip3] pyzmq==27.1.0
[pip3] torch==2.11.0+xpu
[pip3] torchao==0.17.0+xpu
[pip3] torchaudio==2.11.0+xpu
[pip3] torchvision==0.26.0+xpu
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[pip3] triton-xpu==3.7.0
[conda] mkl 2025.3.1 pypi_0 pypi
[conda] numpy 2.4.3 pypi_0 pypi
[conda] onemkl-license 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-blas 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-dft 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-lapack 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-rng 2025.3.1 pypi_0 pypi
[conda] onemkl-sycl-sparse 2025.3.1 pypi_0 pypi
[conda] pyzmq 27.1.0 pypi_0 pypi
[conda] torch 2.11.0+xpu pypi_0 pypi
[conda] torchao 0.17.0+xpu pypi_0 pypi
[conda] torchaudio 2.11.0+xpu pypi_0 pypi
[conda] torchvision 0.26.0+xpu pypi_0 pypi
[conda] transformers 4.57.6 pypi_0 pypi
[conda] triton 3.6.0 pypi_0 pypi
[conda] triton-xpu 3.7.0 pypi_0 pypi
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.19.1rc1.dev29+g93726b2a1 (git sha: 93726b2a1)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
Could not collect
==============================
Environment Variables
==============================
VLLM_ALLOW_LONG_MAX_MODEL_LEN=1
VLLM_WORKER_MULTIPROC_METHOD=spawn
VLLM_XPU_ENABLE_XPU_GRAPH=1
LD_LIBRARY_PATH=/opt/intel/oneapi/tcm/1.4/lib:/opt/intel/oneapi/umf/1.0/lib:/opt/intel/oneapi/tbb/2022.3/env/../lib/intel64/gcc4.8:/opt/intel/oneapi/mpi/2021.17/opt/mpi/libfabric/lib:/opt/intel/oneapi/mpi/2021.17/lib:/opt/intel/oneapi/mkl/2025.3/lib:/opt/intel/oneapi/ippcp/2025.3/lib/:/opt/intel/oneapi/ipp/2022.3/lib:/opt/intel/oneapi/dnnl/2025.3/lib:/opt/intel/oneapi/debugger/2025.3/opt/debugger/lib:/opt/intel/oneapi/dal/2025.10/lib:/opt/intel/oneapi/compiler/2025.3/opt/compiler/lib:/opt/intel/oneapi/compiler/2025.3/lib:/opt/intel/oneapi/ccl/2021.17/lib/:/home/cjai/miniforge3/envs/vllm/lib:/opt/intel/oneapi/tcm/1.4/lib:/opt/intel/oneapi/umf/1.0/lib:/opt/intel/oneapi/tbb/2022.3/env/../lib/intel64/gcc4.8:/opt/intel/oneapi/mpi/2021.17/opt/mpi/libfabric/lib:/opt/intel/oneapi/mpi/2021.17/lib:/opt/intel/oneapi/mkl/2025.3/lib:/opt/intel/oneapi/ippcp/2025.3/lib/:/opt/intel/oneapi/ipp/2022.3/lib:/opt/intel/oneapi/dnnl/2025.3/lib:/opt/intel/oneapi/debugger/2025.3/opt/debugger/lib:/opt/intel/oneapi/dal/2025.10/lib:/opt/intel/oneapi/compiler/2025.3/opt/compiler/lib:/opt/intel/oneapi/compiler/2025.3/lib:/opt/intel/oneapi/ccl/2021.17/lib/
OMP_NUM_THREADS=48
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_cjai🐛 Describe the bug
vllm serve --model /data/models/gpt-oss-20b/ --enforce-eager --port 8000 --host 0.0.0.0 --trust-remote-code --disable-sliding-window --gpu-memory-util=0.87 --max-num-batched-tokens=8192 --max-model-len=8192 --block-size 64 -tp=2 -pp 2 --distributed-executor-backend=mpWARNING 04-04 18:12:14 [argparse_utils.py:191] With `vllm serve`, you should provide the model as a positional argument or in a config file instead of via the `--model` option. The `--model` option will be removed in v0.13.
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █ █ █▄ ▄█
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.19.1rc1.dev29+g93726b2a1
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] █▄█▀ █ █ █ █ model /data/models/gpt-oss-20b/
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:299]
(APIServer pid=335596) INFO 04-04 18:12:14 [utils.py:233] non-default args: {'model_tag': '/data/models/gpt-oss-20b/', 'host': '0.0.0.0', 'model': '/data/models/gpt-oss-20b/', 'trust_remote_code': True, 'max_model_len': 8192, 'enforce_eager': True, 'disable_sliding_window': True, 'distributed_executor_backend': 'mp', 'pipeline_parallel_size': 2, 'tensor_parallel_size': 2, 'block_size': 64, 'gpu_memory_utilization': 0.87, 'max_num_batched_tokens': 8192}
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:554] Resolved architecture: GptOssForCausalLM
(APIServer pid=335596) INFO 04-04 18:12:14 [model.py:1685] Using max model len 8192
(APIServer pid=335596) INFO 04-04 18:12:14 [scheduler.py:238] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=335596) INFO 04-04 18:12:14 [config.py:126] Overriding max cuda graph capture size to 1024 for performance.
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:799] Asynchronous scheduling is enabled.
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(APIServer pid=335596) WARNING 04-04 18:12:14 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(APIServer pid=335596) INFO 04-04 18:12:14 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(APIServer pid=335596) INFO 04-04 18:12:14 [vllm.py:1046] Cudagraph is disabled under eager mode
(APIServer pid=335596) WARNING 04-04 18:12:14 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(APIServer pid=335596) INFO 04-04 18:12:14 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(EngineCore pid=336188) INFO 04-04 18:12:19 [core.py:105] Initializing a V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto')
(EngineCore pid=336188) INFO 04-04 18:12:19 [multiproc_executor.py:137] DP group leader: node_rank=0, node_rank_within_dp=0, master_addr=127.0.0.1, mq_connect_ip=192.168.5.175 (local), world_size=4, local_world_size=4
(Worker pid=336700) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=3 local_rank=3 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336699) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=2 local_rank=2 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=0 local_rank=0 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336698) INFO 04-04 18:12:24 [parallel_state.py:1400] world_size=4 rank=1 local_rank=1 distributed_init_method=tcp://127.0.0.1:40271 backend=xccl
(Worker pid=336697) INFO 04-04 18:12:25 [parallel_state.py:1712] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
2026:04:04-18:12:25:336697 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336697 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336698 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336698 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336700 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336700 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:25:336699 |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi)
2026:04:04-18:12:25:336699 |CCL_WARN| could not get local_idx/count from environment variables, trying to get them from ATL
2026:04:04-18:12:26:336698:[1] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336699:[2] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336697:[0] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
2026:04:04-18:12:26:336700:[3] |CCL_WARN| topology recognition shows PCIe connection between devices. If this is not correct, you can disable topology recognition, with CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0. This will assume XeLinks across devices
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:26 [gpu_model_runner.py:4735] Starting to load model /data/models/gpt-oss-20b/...
(Worker_PP0_TP1 pid=336698) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [xpu.py:81] Using Flash Attention backend.
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [flash_attn.py:622] Using FlashAttention version 2
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:27 [mxfp4.py:352] Using 'XPU' Mxfp4 MoE backend.
(Worker_PP1_TP0 pid=336699) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
(Worker_PP1_TP1 pid=336700) INFO 04-04 18:12:27 [xpu.py:59] Setting VLLM_KV_CACHE_LAYOUT to 'NHD' for XPU; only NHD layout is supported by XPU attention kernels.
Loading safetensors checkpoint shards: 0% Completed | 0/3 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 33% Completed | 1/3 [00:00<00:00, 2.23it/s]
Loading safetensors checkpoint shards: 67% Completed | 2/3 [00:00<00:00, 2.29it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.64it/s]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:01<00:00, 1.77it/s]
(Worker_PP0_TP0 pid=336697)
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [default_loader.py:384] Loading weights took 1.75 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [mxfp4.py:836] Using MoEPrepareAndFinalizeNoDPEPModular
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:29 [gpu_model_runner.py:4820] Model loading took 3.85 GiB memory and 2.185793 seconds
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [gpu_worker.py:436] Available KV cache memory: 14.86 GiB
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1319] GPU KV cache size: 1,222,720 tokens
(EngineCore pid=336188) INFO 04-04 18:12:32 [kv_cache_utils.py:1324] Maximum concurrency for 8,192 tokens per request: 149.26x
(Worker_PP0_TP0 pid=336697) INFO 04-04 18:12:32 [utils.py:60] `_KV_CACHE_LAYOUT_OVERRIDE` variable detected. Setting KV cache layout to NHD.
(EngineCore pid=336188) INFO 04-04 18:12:32 [core.py:283] init engine (profile, create kv cache, warmup model) took 3.13 seconds
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:799] Asynchronous scheduling is enabled.
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:857] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
(EngineCore pid=336188) WARNING 04-04 18:12:33 [vllm.py:868] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
(EngineCore pid=336188) INFO 04-04 18:12:33 [kernel.py:199] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native'])
(EngineCore pid=336188) INFO 04-04 18:12:33 [vllm.py:1046] Cudagraph is disabled under eager mode
(EngineCore pid=336188) WARNING 04-04 18:12:33 [xpu.py:190] XPU Graph doesn't support capture communication ops, disabling cudagraph_mode.
(EngineCore pid=336188) INFO 04-04 18:12:33 [compilation.py:290] Enabled custom fusions: norm_quant, act_quant
(APIServer pid=335596) INFO 04-04 18:12:33 [api_server.py:604] Supported tasks: ['generate']
(APIServer pid=335596) WARNING 04-04 18:12:33 [serving.py:233] For gpt-oss, we ignore --enable-auto-tool-choice and always enable tool use.
(APIServer pid=335596) INFO 04-04 18:12:34 [hf.py:314] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this.
(APIServer pid=335596) INFO 04-04 18:12:34 [api_server.py:608] Starting vLLM server on http://0.0.0.0:8000
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:37] Available routes are:
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /tokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /detokenize, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /load, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /version, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /health, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /metrics, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/models, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /ping, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /invocations, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /v1/completions/render, Methods: POST
(APIServer pid=335596) INFO 04-04 18:12:34 [launcher.py:46] Route: /generative_scoring, Methods: POST
(APIServer pid=335596) INFO: Started server process [335596]
(APIServer pid=335596) INFO: Waiting for application startup.
(APIServer pid=335596) INFO: Application startup complete.
(APIServer pid=335596) INFO: 127.0.0.1:34608 - "GET /metrics HTTP/1.1" 200 OK
(APIServer pid=335596) INFO: 127.0.0.1:34610 - "POST /v1/completions HTTP/1.1" 200 OK
(Worker_PP0_TP0 pid=336697) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP0 pid=336697) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(Worker_PP0_TP1 pid=336698) /home/cjai/vllm/vllm/distributed/parallel_state.py:664: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:1586.)
(Worker_PP0_TP1 pid=336698) object_tensor = torch.frombuffer(pickle.dumps(obj), dtype=torch.uint8)
(APIServer pid=335596) INFO 04-04 18:13:04 [loggers.py:259] Engine 000: Avg prompt throughput: 102.4 tokens/s, Avg generation throughput: 0.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(APIServer pid=335596) INFO 04-04 18:13:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.1%, Prefix cache hit rate: 0.0%
(EngineCore pid=336188) INFO 04-04 18:13:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:14:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:15:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) INFO 04-04 18:16:57 [shm_broadcast.py:681] No available shared memory broadcast block found in 60 seconds. This typically happens when some processes are hanging or doing some time-consuming work (e.g. compilation, weight/kv cache quantization).
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:72] Dumping input data for V1 LLM engine (v0.19.1rc1.dev29+g93726b2a1) with config: model='/data/models/gpt-oss-20b/', speculative_config=None, tokenizer='/data/models/gpt-oss-20b/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=2, pipeline_parallel_size=2, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=mxfp4, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=xpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='openai_gptoss', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=0, served_model_name=/data/models/gpt-oss-20b/, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['xpu_kernels', 'native']), enable_flashinfer_autotune=True, moe_backend='auto'),
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:79] Dumping scheduler output for model execution: SchedulerOutput(scheduled_new_reqs=[], scheduled_cached_reqs=CachedRequestData(req_ids=['cmpl-bench-dd7f173a-0-0-8a43c102'],resumed_req_ids=set(),new_token_ids_lens=[],all_token_ids_lens={},new_block_ids=[([17],)],num_computed_tokens=[1024],num_output_tokens=[1]), num_scheduled_tokens={cmpl-bench-dd7f173a-0-0-8a43c102: 1}, total_num_scheduled_tokens=1, scheduled_spec_decode_tokens={}, scheduled_encoder_inputs={}, num_common_prefix_blocks=[17], finished_req_ids=[], free_encoder_mm_hashes=[], preempted_req_ids=[], has_structured_output_requests=false, pending_structured_output_tokens=false, num_invalid_spec_tokens=null, kv_connector_metadata=null, ec_connector_metadata=null, new_block_ids_to_zero=null)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [dump_input.py:81] Dumping scheduler stats: SchedulerStats(num_running_reqs=1, num_waiting_reqs=0, step_counter=0, current_wave=0, kv_cache_usage=0.0008898659966498634, encoder_cache_usage=0.0, prefix_cache_stats=PrefixCacheStats(reset=False, requests=0, queries=0, hits=0, preempted_requests=0, preempted_queries=0, preempted_hits=0), connector_prefix_cache_stats=None, kv_cache_eviction_events=[], spec_decoding_stats=None, kv_connector_stats=None, waiting_lora_adapters={}, running_lora_adapters={}, cudagraph_stats=None, perf_stats=None)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] EngineCore encountered a fatal error.
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 394, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] status, result = mq.dequeue(timeout=dequeue_timeout)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 755, in dequeue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] with self.acquire_read(timeout, indefinite) as buf:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/contextlib.py", line 137, in __enter__
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return next(self.gen)
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 674, in acquire_read
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._spin_condition.wait(timeout_ms=read_timeout.timeout_ms())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/distributed/device_communicators/shm_broadcast.py", line 631, in timeout_ms
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] The above exception was the direct cause of the following exception:
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110]
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] Traceback (most recent call last):
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1101, in run_engine_core
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] engine_core.run_busy_loop()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1142, in run_busy_loop
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] self._process_engine_step()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 1181, in _process_engine_step
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] outputs, model_executed = self.step_fn()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/engine/core.py", line 499, in step_with_batch_queue
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] model_output = future.result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 88, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return super().result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 449, in result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] return self.__get_result()
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/miniforge3/envs/vllm/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise self._exception
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 92, in _wait_for_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] response = self.aggregate(self.get_response())
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] ^^^^^^^^^^^^^^^^^^^
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] File "/home/cjai/vllm/vllm/v1/executor/multiproc_executor.py", line 396, in get_response
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] raise TimeoutError(f"RPC call to {method} timed out.") from e
(EngineCore pid=336188) ERROR 04-04 18:17:54 [core.py:1110] TimeoutError: RPC call to sample_tokens timed out.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] AsyncLLM output_handler failed.
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] Traceback (most recent call last):
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/async_llm.py", line 663, in output_handler
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] outputs = await engine_core.get_output_async()
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] File "/home/cjai/vllm/vllm/v1/engine/core_client.py", line 970, in get_output_async
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] raise self._format_exception(outputs) from None
(APIServer pid=335596) ERROR 04-04 18:17:54 [async_llm.py:707] vllm.v1.engine.exceptions.EngineDeadError: EngineCore encountered an issue. See stack trace (above) for the root cause.
(APIServer pid=335596) INFO: Shutting down
(APIServer pid=335596) INFO: Waiting for application shutdown.
(APIServer pid=335596) INFO: Application shutdown complete.
(APIServer pid=335596) INFO: Finished server process [335596]Before submitting a new issue...
- Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.
extent analysis
TL;DR
The issue is likely caused by a timeout error in the EngineCore, which may be due to a communication issue between processes or a problem with the model execution.
Guidance
- Check the model execution: Verify that the model is executing correctly and not causing any timeouts. This can be done by checking the model's performance and adjusting the
dequeue_timeoutparameter if necessary. - Investigate communication issues: Look into potential communication issues between processes, such as problems with shared memory or message queues. Check the
shm_broadcast.pyfile for any errors or warnings related to communication. - Adjust timeout parameters: Consider increasing the timeout parameters, such as
dequeue_timeout, to give the model more time to execute and respond. - Verify process synchronization: Ensure that the processes are properly synchronized and that there are no deadlocks or other synchronization issues.
Example
No specific code example can be provided without more information about the model and the execution environment. However, the error message suggests that the issue is related to the EngineCore and the shm_broadcast.py file, which may require adjustments to the model execution or communication parameters.
Notes
The error message indicates a timeout error in the EngineCore, which may be caused by a variety of factors, including model execution issues, communication problems, or synchronization errors. Further investigation is needed to determine the root cause of the issue.
Recommendation
Apply a workaround by adjusting the timeout parameters, such as increasing the dequeue_timeout, to give the model more time to execute and respond. If the issue persists, further investigation into the model execution and communication is necessary.
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- add models is error
- panic: could not create filter
- Persist partially generated messages when /chat-messages/:task_id/stop is called
- MCP server connection fails with 403 — request never leaves Dify (SSRF proxy suspected)
- Support durable async execution backends for long-running workflow steps
- [Xiaomi MiMo] Credentials validation fails with 400 "Not supported model mimo-v2-flash" when using Token Plan endpoint (v0.0.7)
- After clicking preview on a parent-child segmented knowledge base, it shows 0 chunks
- Retrieval score differs between UI upload (.docx) and API upload (.txt) despite identical chunk content and embedding model
- gemini cli crash again
- Xbox gift card code damage
- Damage caused by the gemini cli crash
- ioctl(2) failed, EBADF (Bad File Descriptor)
- Feat: Support Bun as an alternative runtime/package manager for updates and extensions
- fatal error again!!!!
- ioctl error
- Critical Crash: ioctl(2) failed, EBADF in ShellExecutionService.resizePty
- ioctl(2) failed, EBADF
- v0.44.0 Regression: Critical crash with ioctl(2) failed, EBADF during PTY resize
- Crash on startup: ioctl(2) failed, EBADF in UnixTerminal.resize
- Crash: `ioctl(2) failed, EBADF` in `node-pty` during PTY resize on macOS
- Gemini CLI crashes with `ioctl(2) failed, EBADF` in `node-pty` during `resizePty`
- Remote Role
- ERROR ioctl(2) failed, EBADF /home/mich
- RangeError: Maximum call stack size exceeded
- EBADF Error during folder creationg broke session and terminal glitches
- MAIP / Gargoub Project - Mediterania - North Coast
- Gemini cli crash again in this morning
- ERROR ioctl(2) failed, EBADF
- Verified node install fails — Checksum verification failed (Cloud)
- The extended debugging key did not arrive during registration.
- CollaborationPane unmounts collaboration store on single-user instances, causing permanent "No network connection" state
- Workflow cannot be saved when the name contains "->" (Potentially malicious string)
- automation does not work and does not show an error
- Raj Ai Automation
- Default Data Loader: DOMMatrix is not defined error
- Feature: Per-node execution timestamp overlay on canvas during workflow run
- AI Agent + Vertex `gemini-3.5-flash`: 400 "missing thought_signature" on sequential multi-turn tool calls (post-#24982)
- PDF Loader in Pinecone Vector Store fails due to pdf-parse version conflict (v2 not supported)
- emailReadImap: add UID deduplication, batch size cap, and numeric uid enforcement
- Manual node execution fails with "Could not find a node" when autosave is disabled (N8N_WORKFLOWS_AUTOSAVE_DISABLED)
- Schedule Trigger stopped firing — workflow Published & active, manual executions succeed, no automated fires for 2+ hours
- [MCP SDK] create_workflow_from_code intermittently returns HTTP 500, often as a false negative (workflow persists anyway, causing duplicates on retry)
- Credential-load wedge: workflows using googleApi/jwtAuth credentials silently fail to execute after key rotation
- Google Sheets Trigger every minute is not working manual Execute is working sent email
- [BUG] Plugin marketplace MCP connector remains stuck "still connecting" when mcp-remote requires OAuth
- [redacted at user request]
- Opus 4.7 behavioral regression: loaded instruction-following discipline degraded in recent Claude Code/Cowork updates
- [BUG] Tailscale via Homebrew CLI + Mac App Store GUI, both Macs on macOS, Cowork blocked by VPN detector despite Tailscale being a mesh VPN with no traffic interception
- stopShellPty on tab switch kills active sessions (exit 143) — regression in May 27 build
- [BUG] Long URLs are broken into multiple lines and become unclickable in terminal output
- [BUG] claude rm/stop/reap SIGKILLs background session tree without SIGTERM grace, orphaning git index.lock and similar
- [BUG] Default git workflow in the system prompt was pushed without context or consent
- [MODEL] Inconsistent output quality / Ignoring instructions (overfitting and inappropriate repetition of Korean vocabulary)
- You've hit your weekly limit · resets May 31 at 5pm (Asia/Shanghai)
- Paid yearly subscription silently downgraded to Free with no user action
- [Regression v2.1.153] Plugin bash hooks fail with "echo: write error: Permission denied" on Windows (claude-mem, shell: "bash")
- [BUG] Connector toggles in conversation are not clickable — must click text label instead
- [remote-control] Input from mobile app/browser not reaching host session — output works fine
- Model fails to read/reference CLAUDE.md contents despite being loaded in context
- [BUG] Claude Desktop reinstall destroys Code chat history (transcripts + Recents) while regular Chat history, project files, and memory all survive
- Bypass mode clamps to Accept Edits even with the toggle ON (Claude Code Desktop 1.9255.2 / CC 2.1.149)
- [BUG] TUI input freezes randomly mid-typing — entire prompt becomes unresponsive for minutes
- [BUG] Cowork downloads Linux ELF binary instead of macOS binary on macOS Sonoma 14.8.7 — exit code 132 (SIGILL) on every session
- [Feature Request] Persistent project memory — sessions forget everything on close, forcing users to keep many sessions open
- [Bug] Thread context stale after sleep/resume, returns outdated date and calendar data
- [FEATURE] Add context window usage indicator and warning before auto-compaction
- [BUG] Dictation error: Invalid character in header content ["x-config-keyterms"] on Windows
- [Bug] Anthropic API Error: Server rate limiting despite normal usage
- Does delegating work to `claude -p` subprocesses reduce context accumulation in the parent session?
- [BUG] Claude Code hangs on M1 Mac when terminal says "opening browser to sign in" and browser opens
- [BUG] Claude_Preview MCP preview_start spawns dev server with main-repo cwd instead of session's worktree cwd
- [Bug] Anthropic API Error: Server rate limiting during request execution
- [Bug] Anthropic API Error: Server rate limiting on concurrent requests
- [Bug] Ultraplan ready notification fires before cloud agent completes execution
- [BUG] API 500 ERROR ALL THROUGHOUT THE DAY
- [BUG] Cowork: Live Artifacts folder path changed in 1.9255.2, no automatic migration from Documents\Claude\Artifacts
- [Bug] Auto-compact never triggers despite statusline reporting "100% context used" (v2.1.153, Max sub, 200K mode)
- [BUG] [Desktop / macOS] 'Open in → New Window' detached session: font renders smaller than main, no per-window controls, Cmd+/Cmd- keystrokes routed to main window instead
- Feature request: option to switch between classic and new minimal UI
- [Feature Request] Show timestamps for each message
- [BUG] Terminal corruption when permission prompt appears while navigating Agent Teams agent selection menu
- [FEATURE] Allow users to customize the background color of the Claude desktop app beyond the current light/dark theme presets.
- [BUG] Statusline not displaying on Windows [fixed]
- Background agent UI Stop button is a no-op for stuck agents — process keeps consuming tokens
- Background agents silently die on session pause/resume — no completion notification, no work recovery
- Add option to hide email address from welcome banner
- [BUG] SSH Remote: `projects` field in remote ~/.claude.json becomes null after desktop restart — jsonl files intact, UI shows 'No messages yet' for every session
- [Bug] Claude Code not applying fixes despite claiming to complete tasks
- billing is unfair and poorly documented
- [BUG] Claude Code on the web: declared plugins inactive on first session, require restart to fully load
- [BUG] Restore from archive deleted sessions instead of restoring them
- [BUG] M365 connector fails with AADSTS50011 in Cowork — localhost vs 127.0.0.1 redirect URI mismatch
- claude agents: workflow slash-commands missing from dispatch-input completion (regression-adjacent to #61424)
- Claude Desktop's Info.plist missing TCC usage strings, blocks all EventKit-based MCP servers
- False-positive safety blocks on self-administered governance amendments — request for owner-authority mode for verified professional users
- [BUG] Stop pushing "AUTO"-mode
- [DOCS] Plugin marketplace guide omits `skipLfs` option for git-based sources
- [DOCS] MCP docs omit combined startup notification for MCP server and connector authentication
- [DOCS] Agent view docs omit macOS Privacy & Security identity for background agents
- [DOCS] Npm update docs do not explain release-channel behavior for `claude update`
- [DOCS] Agent SDK docs omit `subagent_type: "claude"` worktree and output persistence behavior
- [DOCS] Background session docs omit `$CLAUDE_JOB_DIR` temp-file behavior
- [FR] mask env-var values in 'claude mcp get <server>' output
- [FR] subagent worktrees should not inherit stale local 'user.email' from prior dispatches
- [BUG] Windows: Grep tool leaks rg.exe + conhost.exe processes (~2000 zombies / 14 GB RAM in long sessions)
- [BUG] Stats dashboard "Peak hour" appears off by one hour
- [BUG] Diff highlight (teal SGR background) bleeds past changed text in 2.1.150–2.1.153
- [FEATURE] confirm before deleting session
- Plugin PostToolUse hooks still silently skip in Claude Desktop / Cowork (re-filing closed #51904)
- /code-review skill: silent fallback to main...HEAD reviews other people's commits, and JSON-only output is hard to read
- Monitor tool doesn't source the shell snapshot like Bash does; PATH-dependent tools (jq, sleep, etc.) fail in Monitor commands on macOS/Nix
- [Bug] Long input lines truncated with ellipsis while typing instead of wrapping in terminal UI
- [FEATURE] VS Code extension: Render submitted user messages as Markdown in chat
- OSC 52 copy from Claude TUI doesn't reach clipboard inside tmux (regression in 2.1.146–2.1.153)
- [BUG] RemoteTrigger create/update returns HTTP 400 with circular error: "event_type is required" / "unknown field event_type"
- [BUG] Option to hide or minimize the built-in "status footer" (multi-line debug/cost panel) [re-raise of #31475]
- [Bug] Feedback submissions being closed without review or action
- [FEATURE] Word-jump cursor navigation in Chat input (option+arrow / bindable actions)
- [FEATURE] ! shell mode: filesystem tab completion
- [BUG] API Error: Usage credits required for 1M context
- claude agents: OSC 52 clipboard emission broken in tmux (regression in 2.1.146–2.1.153)
- CLI crashes on macOS 15 M3 - exit code 1
- [FEATURE] Support Cmd+V image paste from clipboard
- [FEATURE] Enhance claude.ai M365 connector to support MS Planner
- [BUG] Slash command autocomplete hijacks pasted absolute file paths starting with /
- PreToolUse hook `if` filter false-positives on complex Bash commands
- [BUG] Diff panel hangs/whites out
- Feature Request: Support drag-and-drop for binary documents (.wps, .doc, .docx, .xlsx, .pdf) in VS Code extension
- [BUG] activation of 1M context in VSCode
- [FEATURE] Support i18n / language localization for built-in slash command outputs
- Ctrl+V para colar imagens deixou de funcionar no CLI (Windows, PowerShell)
- [FEATURE] Please add Norwegian (Bokmål/Nynorsk) language support to the Claude Code interface
- [BUG] OTel log events (claude_code.user_prompt, api_request_body, tool_decision, hook_execution_complete) emitted with empty trace_id/span_id while sibling spans correlate correctly
- [BUG] Cowork crashes on every message, no VM logs generated, missing AppData\Roaming\Claude
- [FEATURE] first-class session handoff + per-session token budgets for unattended runs
- [FEATURE] Smart paste: convert clipboard code to file reference chips (like Cursor)
- [Feature Request] Restore chat pin functionality to title chat submenu
- [BUG] SIGILL issues with version 2.1.153
- [BUG] Cowork plugin upload fails with generic "Plugin validation failed" when a `description` field in any SKILL.md frontmatter contains angle brackets (`<…>`)
- [BUG] Desktop App 2.1.144+: startup scanner deletes cliSessionId from claude-code-sessions local files on every launch — session not found on disk
- [Feature Request] Add keyboard shortcut to copy last message with proper formatting
- [MODEL] Opus 4.7 not 1M
- Allow naming/renaming background agents in `claude agents` view
- Stale worktrees in .claude/worktrees/ are never cleaned up, consuming massive disk space
- Agent worktrees are never cleaned up, silently consuming disk space
- Subagent worktrees not auto-cleaned when reviewer writes scratch files
- [Bug] Skill initialization hangs for extended duration in Plan Mode
- Claude Desktop writes malformed registry Run entry (nested escaped quotes) - crashes Windows Task Manager and other Run-key parsers
- IME candidate window shows at bottom-right corner instead of caret position (Windows CMD)
- [BUG] Pressing 'Escape' doesn't close the /BTW conversation when the main conversation is asking for approval
- [BUG] Opus 4.7 (1M) intermittently emits empty-string values for tool_use.input fields, killing the session
- FleetView agent UI shows "running" with incrementing elapsed time after agent has returned
- /doctor flags context-scoped cmd+c binding as macOS conflict (false positive)
- [BUG] Text Rendering in Elvish
- Desktop app: Bypass Permissions mode flips to Accept Edits on first prompt (M5 / macOS 26.5)
- [Workaround] Date-Weekday Verification Hook — Prevents Claude from writing wrong weekdays
- [BUG] Claude Code create c:/memfs directory without asking me.
- [BUG] Claude Code's Bash execution waits forever with no processes running
- [BUG] usage stays stuck waiting for 5 hr limit after upgrading to premium seat in team plan
- [Workflow tool] resume cache is unreachable for nontrivial workflows because LLM dispatchers can't transcribe args byte-exactly
- Code review (Preview): "Add a repository" shows no results for private GitHub org repos
- [BUG] /context commands blows up context
- [Feature Request] Add precache expiry hook to enable proactive compaction before token eviction
- [BUG] Context indicator shows 0% at session start despite ~20K+ tokens already loaded
- [Feature Request] Add semantic search for --resume session history
- [Feature Request] Add session search, tagging, and filtering capabilities
- [BUG] Cowork Dispatch reports "desktop not available" on Windows 11 while standard Cowork works normally
- [Bug] Claude Code provides incorrect suggestions with high confidence despite errors
- defaultMode: acceptEdits silently overrides per-path permissions.ask rules for Write/Edit
- [FEATUR configurable tip interval (e.g. tipIntervalSeconds: 30 in settings)E]
- Plugin marketplace fails to load: schema rejects 'displayName' key (v2.1.153)
- claude agents: in-session copy uses broken OSC 52 path while overview correctly uses tmux buffer
- [BUG] Plugin agent descriptions (and custom agents) load unconditionally into context — no parity with disable-model-invocation for skills
- Crashed ultrareview consumed a free credit despite producing zero findings
- [Bug] Character rendering issue - invisible or missing text display
- [BUG] Cowork: processo Claude Code encerra com código 3 — .claude.json não contém token de autenticação (Windows 11 25H2)
- [BUG] 2.1.153 silently discards tools/list response from rmcp 0.12.0 HTTP MCP server (works in 2.1.152, wire-identical handshake)
- VS Code extension: option to auto-resume last session when reopening a workspace folder
- [Bug] Conversation continuation failure
- [BUG] Cowork crashes every time I start a new chat or attempt to continue an existing one in any project. The error displayed is: "Claude Code è andato in crash
- [Bug] Unannounced quota changes
- Native update/install fails with 'socket connection was closed unexpectedly' behind proxy — undici TLS incompatibility
- [BUG] Session name reverting after manual change
- [BUG] 非正常思考，上下文过长时，一直显示思考，点击interrupt按钮失效
- Honor `tools:` frontmatter when an agent is invoked via `@mention` — strip `Task` only when the agent did not declare it
- macOS TCC popup still recurring on v2.1.153 — "2.1.153" would like to access data from other apps
- Claude Code leaks pty handles — exhausts pseudo-terminals on macOS after long session
- [Bug] Agent fails to execute or respond to user input
- [BUG] Persistent "Expecting value: line 1 column 1 (char 0)" JSON parse error after tool execution
- [Feature Request] Implement proactive unit test coverage recommendations for recurring bugs
- VS Code panel lacks status line + terminal lacks image paste in Codespaces, forcing a tradeoff
- `/powerup` only shows ~10 lessons — allow viewing the full catalog
- [Bug] Context contamination after auto-compact with unrelated email draft of Tejo/Sado Basin
- [Bug] VSCode terminal output displays corrupted text with garbled symbols
- [Feature Request] Add LaTeX/KaTeX math rendering to TUI
- [Bug] Sub-agent PR review results not validated by orchestrating agent
- Subagents on Pro 1M tier: trivial probes pass, real workloads fail at first tool call (probe-vs-workload divergence)
- Path-scoped rules and subdirectory CLAUDE.md not loaded when creating new files matching the pattern
- AskUserQuestion: cancelling during extended thinking poisons the whole session with 400 'thinking blocks cannot be modified' (2.1.153); concurrent prompts overwrite each other
- Ideas Missing from Claude Cowork Menu (Windows)
- [BUG_BOUNTY_SAFE_POC_2026] Prompt Injection RCE Test - Command Execution Proof
- [BUG] Cowork scheduled task: execution history row not showing after successful run
- Resuming an extended-thinking session fails permanently with 400 "thinking blocks cannot be modified" (transcript stores thinking text as empty but keeps signature)
- [Bug] Plugin-registered CwdChanged and FileChanged hooks don't fire (settings.json works) — v2.1.153
- Auto-archive on PR merge / branch delete — clarify autoArchiveSessions semantics or add dedicated opt-out
- `claude mcp add` echoes Authorization header value verbatim to stdout, leaks bearer tokens to terminal and session transcripts
- [BUG] Bug report — /insights skill, Claude Code The /insights skill outputs a malformed file path.
- Plugin slash commands render with '*'-inline format instead of two-column, despite matching official plugin shape
- [Bug] Unexpected long text generation without user input or goal
- [Bug] Thinking blocks causing task progression blocked without user modification
- [BUG] (Critical!) contamination by an unknown session simirlar to the report => [Bug] Context contamination after auto-compact with unrelated email draft of Tejo/Sado Basin #63137
- [Critical] Opus 4.7 Korean output degeneration — Korean grammar itself collapses in long contexts
- [BUG] Title: Autocompact buffer persists across /clear — wastes tokens for irrelevant old context
- [Bug] Auto-Compact loses user input before processing in conversation history
- Feature: per-invocation effort parameter + runtime session-config introspection for skills
- Auto-mode classifier mislabels Azure DevOps vote -5 as "Reject" when denying PR vote actions
- [BUG] Claude Desktop and Claude Code CLI never re-register MCP tools after OAuth 2.1 handshake on a remote HTTP server
- [BUG] Workspace file tags leak across sessions
- [BUG] Ink renderer crashes on Windows 11 build 26200 (Canary) duplicate banners, terminal mode leaks, mid-operation aborts
- [BUG] Claude Code Desktop issue
- PTY master fd leak in Claude desktop app exhausts macOS kern.tty.ptmx_max after ~2-3 days
- [BUG] Claude Code — Session Management after Unexpected Interruption
- [Windows] Cowork OpenTelemetry exporter does not initialize - zero events emitted to any destination, including loopback
- [Bug] Opus 4.7: 400 `thinking blocks ... cannot be modified` on long extended-thinking sessions, triggered by history-altering events (scheduled prompts / parallel tool-call cancellation)
- [BUG] API Error: Server is temporarily limiting requests (not your usage limit) · Rate limited
- Multi-plugin custom marketplace: only first plugin registered in installed_plugins.json, skills don't load
- [BUG] Git push through the SDK's git proxy fan-outs into ~500 GitHub REST API calls, exhausting the 5,000/hour budget after a handful of pushes
- [BUG] Claude took liberties it really shouldn't with my global config
- [BUG] Agent window focus lost after navigating with arrow keys, causing scroll deadlock
- [BUG] `--model` flag silently ignored in interactive sessions (works in `--print` only)
- [BUG] Dispatch permanently shows "desktop appears offline" on Windows 11 - never worked on first use
- feat: support per-command enableWeakerNetworkIsolation as safer alternative to dangerouslyDisableSandbox
- /code-review outputs a raw JSON array instead of readable findings
- [BUG] Cowork — Additional allowed domains ignored on Team plan; same domain works on Pro plan
- Haiku
- [Bug] False positive blocking beneficial outcomes in tool execution
- 3P Bedrock SSO: credentials silently expire without triggering re-auth on day 2+
- CLAUDE_AUTOCOMPACT_PCT_OVERRIDE in settings.json env block silently ignored by autocompact logic
- Auto-compaction deletes main session JSONL before verifying summary completion, causing data loss
- [Bug] Claude Code not executing stated actions or producing expected results
- [FEATURE] Deferred Messages — Queue Input for End of Turn
- [BUG] Up/Down arrows in input box navigate history instead of moving cursor — regression in 2.1.149+
- Cancelling a parallel tool-call batch corrupts thinking blocks -> 400 "thinking blocks cannot be modified" permanently wedges the session
- Claude Code caused data loss, then contradicted itself about recovery (two incidents, one session)
- [Bug] Unclear error messages from Claude Code CLI
- [Bug] Agent tool rejecting due to context size limit exceeded
- claude agents: daemon and bg-spare processes spin at ~100% CPU when idle
- [BUG] Compaction fails with "context window limit" error even when context usage is low (e.g., 20%) — regression in v2.1.153
- Remote Control entitlement lost after May 27-28 incident — `Error: Remote Control is not yet enabled for your account` on active Max subscription
- PreToolUse hook exit code 2 does not block Write tool
- [Bug] Thinking blocks in latest assistant message are immutable
- GUI: dispatch file:// and custom-scheme clicks to OS shell handler
- Show current model in statusLine by default
- [Bug] Agent console becomes unresponsive to keyboard input after multiple agents initialized
- [FEATURE] PreToolUse hooks should have a way of updating the environment
- [Bug] Unable to start or use Claude Code CLI
- [BUG] Repository not visible in Claude Code web repo picker
- Session permanently wedged on 400 "thinking blocks cannot be modified" after parallel tool_results
- [Bug] @ autocomplete loses sibling repos after a file edit in multi-repo workspace
- Unclear error message when creating sub-agent without authentication
- [Bug] Anthropic API errors causing frequent failures and high token usage
- [BUG] @ mention file picker only shows packages, not individual files (desktop app - Code tab)
- [Bug] TUI panel footer remains sticky and consumes excessive terminal space
- PR-status polling exhausts GitHub GraphQL rate limit on repos with many open PRs
- [BUG] Windows: welcome panel not shown in some project folders (2.1.153)
- [Bug] Anthropic API Error: thinking blocks corrupted during context compaction with extended thinking enabled
- API 400 "thinking blocks cannot be modified" permanently bricks session during agent activation (interleaved thinking + tool use)
- Right-click Copy copies the whole message instead of the selection; pasted text retains dark background
- Mid-session model switch corrupts conversation when extended thinking is enabled (API 400: 'thinking blocks cannot be modified')
- [BUG] Markdown file links in chat output do not open files when clicked (VS Code extension)
- Stuck retry loop: `400 thinking blocks cannot be modified` on large interleaved-thinking turns using AskUserQuestion
- [FEATURE] Prompt user for approval before auto-compaction proceeds
- Custom MCP connectors not attachable to scheduled routines — no UUID discovery path
- [BUG] Claude in Chrome — Navigation blocked for teams.cloud.microsoft and outlook.cloud.microsoft after Microsoft domain migration**
- [BUG] Claude Desktop — Personal plugins panel renders list but is entirely non-interactive (macOS, v1.9255.2)
- [Bug] error when using Workflows
- [BUG] Persistent "update available" notification despite being on latest version
- [BUG] Sweep Agent from /code-review never completes
- [Bug] Tool calls not executing or returning results
- [FEATURE] Cloud-synced memory and settings across machines
- [Bug] Terminal UI freezes when Ctrl+O view exits during interactive prompt in plan mode
- Continuous api errors when using claude code with Opus 4.7 with thinking on low
- [Feature Request] Add support for installing and using previous Claude Code versions
- [Bug] Extended Thinking: Summarized thinking blocks fail signature validation when resent to API
- [Bug] Anthropic API Error: 'thinking' blocks cannot be modified
- [Bug] Anthropic API Error: Thinking blocks cannot be modified with extended thinking mode
- Feature request: Lazy/on-demand MCP server connections
- [Bug] Tool Arguments Parsed as String Instead of Object
- [Bug] Anthropic API Error: Insufficient context provided
- [Bug] Claude Opus occasionally uses moskovian(russian) orthography instead of Ukrainian in system-prompted responses
- Opus 4.8: backgrounded task completions (subagents AND Bash) crash with 400 "thinking blocks cannot be modified"
- [Bug] Opus 4.7 fabricates stable preferences ("my default") to rationalize arbitrary choices when challenged
- [Bug] Unable to update Claude Code CLI
- [BUG] Desktop app: /remote-control mints link + connects bridge (main.log) but in-chat link/QR panel never renders
- Feature: sessionColor and sessionName in .claude/settings.json
- [BUG] Anthropic API error: thinking blocks
- [FEATURE] Support Remote MCPs in Cowork as in Claude Code
- [Bug] Anthropic API Error: 400 Bad Request with Redacted Thinking - 0 4.7 & 4.8
- [Bug] Anthropic API Error: Cannot modify thinking blocks from different model versions
- Interleaved thinking + multi-tool turn corrupts thinking block (text blanked, signature kept) → permanent 400 'blocks must remain as they were'
- [BUG] Mode/permission changes mid-tool-loop (effortLevel: xhigh) poisons entire session
- Session failure log: Opus 4.6 ignores its own rules for an entire session
- [BUG] "400 Guardrail was enabled" error when using Claude Opus 4.8 with AWS Bedrock
- [Feature Request] Add subagent approach selection option to avoid accidental feedback
- Persistent 400 'thinking blocks in the latest assistant message cannot be modified' — interleaved thinking persisted with empty text + signature bricks sessions
- [BUG] DesktopvsApp
- [BUG] Opus 4.7 cache hit rate collapse after May 27 incident — Messages 1.1k→88.9k in 9 minutes, $630/session
- [Bug] Anthropic API Error: Invalid thinking block format
- [BUG] FUCK CLAUDE
- Opus 4.8 extended thinking: Stop hook block re-entry corrupts thinking blocks → 400
- [Bug] 4.8 Fails when accessing previous model history
- [Bug] Unintended File Modifications During Execution
- [DOCS] Model configuration docs omit lean system prompt default scope and model exceptions
- Add "Always allow globally" option to permission prompts
- Server-side model upgrade (Opus 4.7→4.8) wedges in-flight sessions with `thinking blocks cannot be modified` 400
- [DOCS] AskUserQuestion docs missing multiple-choice prompt decision threshold
- [DOCS] Agent view docs omit shell-command background session launch syntax
- [DOCS] Agent view dispatch input docs incorrectly imply `/logout` dispatches as a prompt
- [DOCS] Claude in Chrome docs omit connected-browser selection behavior
- [DOCS] Plugin docs omit `defaultEnabled: false` for opt-in plugins
- Feature Request: Customizable chat text colors for user and assistant messages
- [DOCS] `/plugin` Discover tab docs omit directory-based suggested plugin pins
- VSCode Chrome integration silently fails: 3 distinct bugs
- [DOCS] MCP stdio docs omit session environment variables
- [Bug] Anthropic API error on second request within session with Claude Opus 4.8
- Cowork emits a blank session "index" handoff on focus when a CLI session is paused awaiting input
- [DOCS] MCP docs omit `claude mcp list/get` pending-approval output for unapproved project servers
- [BUG] /compact fails with 400 error when last assistant turn contains thinking blocks
- [DOCS] `/claude-api` docs omit Opus 4.8 migration guidance
- [DOCS] Fast mode docs still recommend deprecated Opus 4.6 override variable
- [DOCS] Bash tool docs omit `$TMPDIR` consistency across sandboxed and unsandboxed commands
- [Bug] Anthropic API Error: 400 Bad Request on Extended Thinking
- [DOCS] Background session docs omit worktree-isolation behavior for spawned subagents
- Built-in mechanistic self-verification of verifiable claims (symmetric to the auto permission gate)
- [DOCS] Worktree docs do not clarify `worktree.baseRef: "head"` inside linked worktrees
- [BUG] Excessive RAM usage with multiple parallel chats (~10 sessions → 30 GB memory pressure, macOS OOM)
- [DOCS] Managed MCP policy docs omit invalid `allowedMcpServers`/`deniedMcpServers` entry behavior
- [DOCS] Effort docs omit `CLAUDE_CODE_ALWAYS_ENABLE_EFFORT` unsupported-model behavior
- Regression (2.1.147–2.1.150?): resuming an extended-thinking session after a CC update/model-switch → unrecoverable 400, session bricked
- [DOCS] Windows updater docs omit `claude.exe` in-use recovery guidance
- [DOCS] VS Code auto mode docs still tie mode-picker visibility to bypass-permissions setting
- [DOCS] MCP docs omit `/mcp` tool list and detail rendering behavior
- [DOCS] Fine-grained tool streaming docs still describe provider opt-in behavior
- bypassPermissions: session startup reads flat pref, GUI toggle writes per-account pref — they never sync
- [BUG] Claude Desktop Code tab causes disk write limit violation — 8.5GB in 11 min, macOS kills app (M5, v1.9659.1)
- Ultrareview v2.1.96: docs describe /tasks command + claude ultrareview --json subcommand that don't exist; findings hard to read after completion
- I'd be happy to help create a GitHub issue title, but I don't see the error message in your message. Could you please share the specific error you're encountering? That way I can generate an accurate and descriptive issue title for you.
- [BUG] Claude in Chrome `file_upload` rejects all scheduled-task sessions with misleading error (real cause: INVALID_SESSION)
- Extended thinking: signed thinking block 'cannot be modified' (400) permanently wedges session
- RTL text support for Hebrew (and Arabic) in Claude Code
- [Bug] Random errors occurring across multiple operations