ollama - 💡(How to fix) Fix generate completion API hangs with certain models but not with others
ON THIS PAGE
Recommended Tools
×6Utilities matched from this issue’s tags and category — try them while you read without losing context.
GitHub issue graph ai analysis
Paste a GitHub issue URL. We fetch that issue, discover linked issues from bodies/comments/timeline, collect linked pull requests, and produce a structured English report.
The report is written in English Markdown for sharing and archival.
Helpful · Quick feedback
Error Message
time=2026-05-08T18:24:02.280+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35 time=2026-05-08T18:32:43.540+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35 time=2026-05-08T18:38:25.054+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35 time=2026-05-08T18:41:08.341+02:00 level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=262144 n_ctx_train=131072
Code Example
time=2026-05-08T18:24:02.280+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:24:02.320+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:24:02.320+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49335"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.4 GiB" free_swap="0 B"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:24:02.379+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:24:02.379+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49335"
time=2026-05-08T18:24:02.382+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:02.407+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.019 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:24:02.439+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:24:03.227+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:24:04.482+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:24:04.483+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:24:05.237+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.91 seconds"
[GIN] 2026/05/08 - 18:25:21 | 200 | 804.167µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:25:21 | 200 | 46µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:31:26 | 200 | 16.125µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:31:26 | 200 | 6.700084ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:31:26 | 200 | 6.635458ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:32:06 | 200 | 13.042µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:32:06 | 200 | 18.125µs | 127.0.0.1 | GET "/api/ps"
time=2026-05-08T18:32:08.392+02:00 level=INFO source=model_recommendations.go:177 msg="model recommendations cache sleep scheduled" wait=3h32m45.889623412s consecutive_failures=0
[GIN] 2026/05/08 - 18:32:42 | 200 | 8m40s | 129.152.22.122 | POST "/api/generate"
time=2026-05-08T18:32:43.540+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:32:43.579+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:32:43.579+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49346"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="49.2 GiB" free_swap="0 B"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:32:43.612+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:32:43.612+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49346"
time=2026-05-08T18:32:43.613+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:43.637+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.006 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:32:43.652+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:32:44.441+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:32:45.669+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:32:45.670+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:32:45.921+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.34 seconds"
[GIN] 2026/05/08 - 18:34:09 | 200 | 1m26s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:34:56 | 200 | 21.541µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:34:56 | 200 | 42.292µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:35:09 | 200 | 22.375µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:35:09 | 200 | 16.207667ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:35:09 | 200 | 15.012042ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:35:11 | 200 | 19.917µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:35:11 | 200 | 8.083µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:38:24 | 200 | 31.833µs | 129.152.22.122 | GET "/api/version"
time=2026-05-08T18:38:25.054+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:38:25.093+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:38:25.093+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49355"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.6 GiB" free_swap="0 B"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:38:25.126+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:38:25.126+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49355"
time=2026-05-08T18:38:25.127+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:25.151+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.006 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:38:25.165+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:38:25.924+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:38:27.165+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:38:27.166+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:38:27.417+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.32 seconds"
[GIN] 2026/05/08 - 18:39:03 | 200 | 11.125µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:03 | 200 | 18.833µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:39:27 | 200 | 12.916µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:27 | 200 | 7.448292ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:39:27 | 200 | 6.8675ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:39:31 | 200 | 18.667µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:31 | 200 | 32.75µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:39:58 | 200 | 1m33s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:40:18 | 200 | 19.917µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:40:59 | 200 | 55.417µs | 129.152.22.122 | GET "/api/version"
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 7.989 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
llama_model_load_from_file_impl: using device Metal (Apple M4 Pro) (unknown id) - 57343 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llama 3.2 3B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 3B
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 8: llama.block_count u32 = 28
llama_model_loader: - kv 9: llama.context_length u32 = 131072
llama_model_loader: - kv 10: llama.embedding_length u32 = 3072
llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192
llama_model_loader: - kv 12: llama.attention.head_count u32 = 24
llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 16: llama.attention.key_length u32 = 128
llama_model_loader: - kv 17: llama.attention.value_length u32 = 128
llama_model_loader: - kv 18: general.file_type u32 = 15
llama_model_loader: - kv 19: llama.vocab_size u32 = 128256
llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - type f32: 58 tensors
llama_model_loader: - type q4_K: 168 tensors
llama_model_loader: - type q6_K: 29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 1.87 GiB (5.01 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 1
print_info: no_alloc = 0
print_info: model type = ?B
print_info: model params = 3.21 B
print_info: general.name = Llama 3.2 3B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128001 '<|end_of_text|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2026-05-08T18:41:08.341+02:00 level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=262144 n_ctx_train=131072
time=2026-05-08T18:41:08.341+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --model /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff --port 49363"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.6 GiB" free_swap="0 B"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=server.go:532 msg="loading model" "model layers"=29 requested=-1
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="1.9 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="28.0 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="12.5 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:272 msg="total memory" size="42.4 GiB"
time=2026-05-08T18:41:08.376+02:00 level=INFO source=runner.go:965 msg="starting go runner"
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 8.010 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:41:16.395+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2026-05-08T18:41:16.396+02:00 level=INFO source=runner.go:1001 msg="Server listening on 127.0.0.1:49363"
time=2026-05-08T18:41:16.396+02:00 level=INFO source=runner.go:895 msg=load request="{Operation:commit LoraPath:[] Parallel:2 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:29[ID:0 Layers:29(0..28)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:true}"
llama_model_load_from_file_impl: using device Metal (Apple M4 Pro) (unknown id) - 57342 MiB free
time=2026-05-08T18:41:16.397+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:41:16.397+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llama 3.2 3B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 3B
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 8: llama.block_count u32 = 28
llama_model_loader: - kv 9: llama.context_length u32 = 131072
llama_model_loader: - kv 10: llama.embedding_length u32 = 3072
llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192
llama_model_loader: - kv 12: llama.attention.head_count u32 = 24
llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 16: llama.attention.key_length u32 = 128
llama_model_loader: - kv 17: llama.attention.value_length u32 = 128
llama_model_loader: - kv 18: general.file_type u32 = 15
llama_model_loader: - kv 19: llama.vocab_size u32 = 128256
llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - type f32: 58 tensors
llama_model_loader: - type q4_K: 168 tensors
llama_model_loader: - type q6_K: 29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 1.87 GiB (5.01 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 131072
print_info: n_embd = 3072
print_info: n_embd_inp = 3072
print_info: n_layer = 28
print_info: n_head = 24
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 3
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-05
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 8192
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: n_expert_groups = 0
print_info: n_group_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 131072
print_info: rope_yarn_log_mul= 0.0000
print_info: rope_finetuned = unknown
print_info: model type = 3B
print_info: model params = 3.21 B
print_info: general.name = Llama 3.2 3B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128001 '<|end_of_text|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors: CPU_Mapped model buffer size = 308.23 MiB
load_tensors: Metal_Mapped model buffer size = 1918.35 MiB
llama_context: constructing llama_context
llama_context: n_seq_max = 2
llama_context: n_ctx = 262144
llama_context: n_ctx_seq = 131072
llama_context: n_batch = 1024
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = enabled
llama_context: kv_unified = false
llama_context: freq_base = 500000.0
llama_context: freq_scale = 1
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
llama_context: CPU output buffer size = 1.00 MiB
llama_kv_cache: Metal KV buffer size = 28672.00 MiB
llama_kv_cache: size = 28672.00 MiB (131072 cells, 28 layers, 2/2 seqs), K (f16): 14336.00 MiB, V (f16): 14336.00 MiB
llama_context: Metal compute buffer size = 396.01 MiB
llama_context: CPU compute buffer size = 262.01 MiB
llama_context: graph nodes = 931
llama_context: graph splits = 2
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1432 msg="llama runner started in 10.31 seconds"
time=2026-05-08T18:41:18.657+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1432 msg="llama runner started in 10.31 seconds"
[GIN] 2026/05/08 - 18:41:19 | 200 | 19.028101083s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:41:23 | 200 | 20.083µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:41:23 | 200 | 36.708µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:42:04 | 200 | 19.625µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:42:04 | 200 | 383.160792ms | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:42:37 | 200 | 18.125µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:42:37 | 200 | 278.98225ms | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:43:09 | 200 | 18.75µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:12 | 200 | 19.5µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:22 | 200 | 18.583µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:26 | 200 | 18.125µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:36 | 200 | 20.333µs | 129.152.22.122 | GET "/api/version"RAW_BUFFERClick to expand / collapse
What is the issue?
generate completion API "hangs" when request is submitted to model qwen3.5:2b (Q8_0) but executes successfully in less than 2s when submitted to model llama3.2:3b (Q4_K_M) on Ollama 0.23.2 and macOS Tahoe 26.4.1.
After submitting the request to qwen3.5:2b mac's GPU goes up to 100% and keeps spinning forever (I had to kill the process with kill -9 after 5 minutes).
This happens regardless of the prompt.
Relevant log output
time=2026-05-08T18:24:02.280+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:24:02.320+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:24:02.320+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49335"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.4 GiB" free_swap="0 B"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:24:02.322+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:24:02.379+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:24:02.379+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49335"
time=2026-05-08T18:24:02.382+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:02.407+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.019 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:24:02.439+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:24:03.227+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:24:04.482+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:24:04.482+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:24:04.483+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:24:05.237+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.91 seconds"
[GIN] 2026/05/08 - 18:25:21 | 200 | 804.167µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:25:21 | 200 | 46µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:31:26 | 200 | 16.125µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:31:26 | 200 | 6.700084ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:31:26 | 200 | 6.635458ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:32:06 | 200 | 13.042µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:32:06 | 200 | 18.125µs | 127.0.0.1 | GET "/api/ps"
time=2026-05-08T18:32:08.392+02:00 level=INFO source=model_recommendations.go:177 msg="model recommendations cache sleep scheduled" wait=3h32m45.889623412s consecutive_failures=0
[GIN] 2026/05/08 - 18:32:42 | 200 | 8m40s | 129.152.22.122 | POST "/api/generate"
time=2026-05-08T18:32:43.540+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:32:43.579+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:32:43.579+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49346"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="49.2 GiB" free_swap="0 B"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:32:43.581+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:32:43.612+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:32:43.612+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49346"
time=2026-05-08T18:32:43.613+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:43.637+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.006 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:32:43.652+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:32:44.441+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:32:45.669+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:32:45.669+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:32:45.670+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:32:45.921+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.34 seconds"
[GIN] 2026/05/08 - 18:34:09 | 200 | 1m26s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:34:56 | 200 | 21.541µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:34:56 | 200 | 42.292µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:35:09 | 200 | 22.375µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:35:09 | 200 | 16.207667ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:35:09 | 200 | 15.012042ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:35:11 | 200 | 19.917µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:35:11 | 200 | 8.083µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:38:24 | 200 | 31.833µs | 129.152.22.122 | GET "/api/version"
time=2026-05-08T18:38:25.054+02:00 level=WARN source=sched.go:423 msg="model architecture does not currently support parallel requests" architecture=qwen35
time=2026-05-08T18:38:25.093+02:00 level=INFO source=server.go:259 msg="enabling flash attention"
time=2026-05-08T18:38:25.093+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --ollama-engine --model /Users/flavio/.ollama/models/blobs/sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297 --port 49355"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.6 GiB" free_swap="0 B"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:38:25.094+02:00 level=INFO source=server.go:792 msg="loading model" "model layers"=25 requested=-1
time=2026-05-08T18:38:25.126+02:00 level=INFO source=runner.go:1450 msg="starting ollama engine"
time=2026-05-08T18:38:25.126+02:00 level=INFO source=runner.go:1485 msg="Server listening on 127.0.0.1:49355"
time=2026-05-08T18:38:25.127+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:25.151+02:00 level=INFO source=ggml.go:144 msg="" architecture=qwen35 file_type=Q8_0 name="" description="" num_tensors=728 num_key_values=52
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.006 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:38:25.165+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
time=2026-05-08T18:38:25.924+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=runner.go:1297 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:25[ID:0 Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:490 msg="offloading 24 repeating layers to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:497 msg="offloading output layer to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=ggml.go:502 msg="offloaded 25/25 layers to GPU"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="2.5 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:245 msg="model weights" device=CPU size="523.8 MiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="3.5 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="3.2 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:267 msg="compute graph" device=CPU size="26.7 MiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=device.go:272 msg="total memory" size="9.7 GiB"
time=2026-05-08T18:38:27.165+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:38:27.165+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:38:27.166+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
time=2026-05-08T18:38:27.417+02:00 level=INFO source=server.go:1432 msg="llama runner started in 2.32 seconds"
[GIN] 2026/05/08 - 18:39:03 | 200 | 11.125µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:03 | 200 | 18.833µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:39:27 | 200 | 12.916µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:27 | 200 | 7.448292ms | 127.0.0.1 | POST "/api/show"
[GIN] 2026/05/08 - 18:39:27 | 200 | 6.8675ms | 127.0.0.1 | POST "/api/generate"
[GIN] 2026/05/08 - 18:39:31 | 200 | 18.667µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:39:31 | 200 | 32.75µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:39:58 | 200 | 1m33s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:40:18 | 200 | 19.917µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:40:59 | 200 | 55.417µs | 129.152.22.122 | GET "/api/version"
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 7.989 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
llama_model_load_from_file_impl: using device Metal (Apple M4 Pro) (unknown id) - 57343 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llama 3.2 3B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 3B
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 8: llama.block_count u32 = 28
llama_model_loader: - kv 9: llama.context_length u32 = 131072
llama_model_loader: - kv 10: llama.embedding_length u32 = 3072
llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192
llama_model_loader: - kv 12: llama.attention.head_count u32 = 24
llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 16: llama.attention.key_length u32 = 128
llama_model_loader: - kv 17: llama.attention.value_length u32 = 128
llama_model_loader: - kv 18: general.file_type u32 = 15
llama_model_loader: - kv 19: llama.vocab_size u32 = 128256
llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - type f32: 58 tensors
llama_model_loader: - type q4_K: 168 tensors
llama_model_loader: - type q6_K: 29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 1.87 GiB (5.01 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 1
print_info: no_alloc = 0
print_info: model type = ?B
print_info: model params = 3.21 B
print_info: general.name = Llama 3.2 3B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128001 '<|end_of_text|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2026-05-08T18:41:08.341+02:00 level=WARN source=server.go:169 msg="requested context size too large for model" num_ctx=262144 n_ctx_train=131072
time=2026-05-08T18:41:08.341+02:00 level=INFO source=server.go:433 msg="starting runner" cmd="/Applications/Ollama.app/Contents/Resources/ollama runner --model /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff --port 49363"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=sched.go:484 msg="system memory" total="64.0 GiB" free="47.6 GiB" free_swap="0 B"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=sched.go:491 msg="gpu memory" id=0 library=Metal available="51.3 GiB" free="51.8 GiB" minimum="512.0 MiB" overhead="0 B"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=server.go:532 msg="loading model" "model layers"=29 requested=-1
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:240 msg="model weights" device=Metal size="1.9 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:251 msg="kv cache" device=Metal size="28.0 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:262 msg="compute graph" device=Metal size="12.5 GiB"
time=2026-05-08T18:41:08.344+02:00 level=INFO source=device.go:272 msg="total memory" size="42.4 GiB"
time=2026-05-08T18:41:08.376+02:00 level=INFO source=runner.go:965 msg="starting go runner"
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 8.010 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M4 Pro
ggml_metal_device_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4 (5002)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 60129.54 MB
load_backend: loaded CPU backend from /Applications/Ollama.app/Contents/Resources/libggml-cpu.so
time=2026-05-08T18:41:16.395+02:00 level=INFO source=ggml.go:104 msg=system Metal.0.EMBED_LIBRARY=1 CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.FP16_VA=1 CPU.0.DOTPROD=1 CPU.0.LLAMAFILE=1 CPU.0.ACCELERATE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.FP16_VA=1 CPU.1.DOTPROD=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2026-05-08T18:41:16.396+02:00 level=INFO source=runner.go:1001 msg="Server listening on 127.0.0.1:49363"
time=2026-05-08T18:41:16.396+02:00 level=INFO source=runner.go:895 msg=load request="{Operation:commit LoraPath:[] Parallel:2 BatchSize:512 FlashAttention:Enabled KvSize:262144 KvCacheType: NumThreads:10 GPULayers:29[ID:0 Layers:29(0..28)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:true}"
llama_model_load_from_file_impl: using device Metal (Apple M4 Pro) (unknown id) - 57342 MiB free
time=2026-05-08T18:41:16.397+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:41:16.397+02:00 level=INFO source=server.go:1428 msg="waiting for server to become available" status="llm server loading model"
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /Users/flavio/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llama 3.2 3B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 3B
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 7: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 8: llama.block_count u32 = 28
llama_model_loader: - kv 9: llama.context_length u32 = 131072
llama_model_loader: - kv 10: llama.embedding_length u32 = 3072
llama_model_loader: - kv 11: llama.feed_forward_length u32 = 8192
llama_model_loader: - kv 12: llama.attention.head_count u32 = 24
llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 16: llama.attention.key_length u32 = 128
llama_model_loader: - kv 17: llama.attention.value_length u32 = 128
llama_model_loader: - kv 18: general.file_type u32 = 15
llama_model_loader: - kv 19: llama.vocab_size u32 = 128256
llama_model_loader: - kv 20: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 22: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 26: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 28: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - type f32: 58 tensors
llama_model_loader: - type q4_K: 168 tensors
llama_model_loader: - type q6_K: 29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 1.87 GiB (5.01 BPW)
load: printing all EOG tokens:
load: - 128001 ('<|end_of_text|>')
load: - 128008 ('<|eom_id|>')
load: - 128009 ('<|eot_id|>')
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 131072
print_info: n_embd = 3072
print_info: n_embd_inp = 3072
print_info: n_layer = 28
print_info: n_head = 24
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 3
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-05
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 8192
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: n_expert_groups = 0
print_info: n_group_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 131072
print_info: rope_yarn_log_mul= 0.0000
print_info: rope_finetuned = unknown
print_info: model type = 3B
print_info: model params = 3.21 B
print_info: general.name = Llama 3.2 3B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 128256
print_info: n_merges = 280147
print_info: BOS token = 128000 '<|begin_of_text|>'
print_info: EOS token = 128009 '<|eot_id|>'
print_info: EOT token = 128001 '<|end_of_text|>'
print_info: EOM token = 128008 '<|eom_id|>'
print_info: LF token = 198 'Ċ'
print_info: EOG token = 128001 '<|end_of_text|>'
print_info: EOG token = 128008 '<|eom_id|>'
print_info: EOG token = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors: CPU_Mapped model buffer size = 308.23 MiB
load_tensors: Metal_Mapped model buffer size = 1918.35 MiB
llama_context: constructing llama_context
llama_context: n_seq_max = 2
llama_context: n_ctx = 262144
llama_context: n_ctx_seq = 131072
llama_context: n_batch = 1024
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = enabled
llama_context: kv_unified = false
llama_context: freq_base = 500000.0
llama_context: freq_scale = 1
ggml_metal_init: allocating
ggml_metal_init: picking default device: Apple M4 Pro
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
llama_context: CPU output buffer size = 1.00 MiB
llama_kv_cache: Metal KV buffer size = 28672.00 MiB
llama_kv_cache: size = 28672.00 MiB (131072 cells, 28 layers, 2/2 seqs), K (f16): 14336.00 MiB, V (f16): 14336.00 MiB
llama_context: Metal compute buffer size = 396.01 MiB
llama_context: CPU compute buffer size = 262.01 MiB
llama_context: graph nodes = 931
llama_context: graph splits = 2
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1432 msg="llama runner started in 10.31 seconds"
time=2026-05-08T18:41:18.657+02:00 level=INFO source=sched.go:561 msg="loaded runners" count=1
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1385 msg="waiting for llama runner to start responding"
time=2026-05-08T18:41:18.657+02:00 level=INFO source=server.go:1432 msg="llama runner started in 10.31 seconds"
[GIN] 2026/05/08 - 18:41:19 | 200 | 19.028101083s | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:41:23 | 200 | 20.083µs | 127.0.0.1 | HEAD "/"
[GIN] 2026/05/08 - 18:41:23 | 200 | 36.708µs | 127.0.0.1 | GET "/api/ps"
[GIN] 2026/05/08 - 18:42:04 | 200 | 19.625µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:42:04 | 200 | 383.160792ms | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:42:37 | 200 | 18.125µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:42:37 | 200 | 278.98225ms | 129.152.22.122 | POST "/api/generate"
[GIN] 2026/05/08 - 18:43:09 | 200 | 18.75µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:12 | 200 | 19.5µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:22 | 200 | 18.583µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:26 | 200 | 18.125µs | 129.152.22.122 | GET "/api/version"
[GIN] 2026/05/08 - 18:43:36 | 200 | 20.333µs | 129.152.22.122 | GET "/api/version"OS
macOS
GPU
Apple
CPU
Apple
Ollama version
0.23.2
Vote matrix · Quick signals
Works
Did the solution work? Tap to confirm.
Easy Fix
Was it a quick fix?
Time Saver
Did it save you time?
Blocking
Was it severely blocking?
Common Issue
Are others likely hitting this too?
Flaky / Intermittent
Is it intermittent?
Verified / Reproducible
Can you reproduce it reliably?
Still need to ship something?
×6Another batch ranked right after the header list — different links, same matching logic.
TRENDING
- Feature Request: Configurable per-minute rate limiting (RPM) for models to prevent 429 errors
- Android: Hermes App + Termux install share ~/.hermes and cause silent permission loops
- hermes update emits unicode-animations ANSI demo in non-interactive logs
- hermes update downgrades aiohttp from 3.13.4 to 3.13.3
- npm install warns about deprecated @babel/plugin-proposal-private-methods
- DingTalk inbound media URLs are skipped as unreadable native image paths
- fix(dashboard): ChatPage clears header action buttons on ALL pages, not just Sessions
- [Bug]: check_web_api_key() hardcodes built-in backends — third-party web search plugins silently disabled
- Hermes Web UI 修复经验：GatewayManager 补丁、进程 D 状态、数据库升级问题
- Telegram gateway can silently drop turn after /stop with response=0 chars while internal work continues
- Bug Report: v0.14.0 上下文污染 — 历史回复碎片回注到新请求
- Bug: hermes skills search table truncates Identifier column — install fails with copied value
- [skills-index-watchdog] Skills index is stale or degraded (degraded)
- Discord approval embed not rendering on web/mobile — embed data present in API but invisible
- Idea: Discord voice-channel participation / opt-in auto-join mode
- [Feature]: Claude Code--ultrawork
- build-arm64 job deterministically fails on cold cache (Azure SAS token expires mid-build)
- [Enhancement] computer_use: action=type should fall back to key events for terminal emulators (Ghostty/Terminal.app/iTerm2)
- Feature Request: Session Recovery on Temporary Provider Outage
- [Bug]: Hermes dashboard not working on NixOS (container)
- [Feature]: Add option to ignore @all/@everyone mentions in Feishu group chats
- QQ Bot WebSocket 频繁断开：长时间工具执行阻塞 asyncio 事件循环导致心跳超时
- patch tool: new_string escape sequences (\t) get written literally
- Feature Request: i18n / 多语言支持（国际化）
- Bug: web_crawl schema lets models auto-guess "instructions" instead of asking the user via clarify
- feat: `!command` prefix for direct shell execution (like Claude Code)
- Expose currently-running cron jobs via /api/jobs (or new endpoint)
- [Bug]: Kanban parent-child handoff: scratch workspace GC destroys artifacts before child can read them
- [Bug, Windows] hermes gateway restart loses session context — planned_stop_marker not written before SIGTERM
- [Bug]: Codex→DeepSeek fallback sends assistant turns without reasoning_content → HTTP 400 (require-side cross-provider failover)
- [Bug]: Update got stuck half way, reboot it, then ModuleNotFoundError: No module named 'hermes_cli'
- Kanban dispatcher corrupt-board handling and multi-profile gateway ownership ambiguity
- Gateway can resend a short fallback message when the real final Telegram response was already delivered
- [BUG] Bedrock: Fix 'Invalid API Key format' for presigned URL tokens
- Secret redaction corrupts code syntax in tool output (write_file, execute_code, terminal)
- Unable to connect Ollama Cloud with Pro Subscription to Hermes
- feat: fuzzy substring matching for /skill autocomplete
- PRD: Autonomous market-impact prediction briefing system
- Kanban dashboard should support task/card deep links
- [Feature] Native Feishu CardKit Streaming: consolidate best-in-class implementations
- [Feature]: Inject mental model into context when using Hindsight
- Interactive CLI hides tool output despite display.tool_progress=all, and hermes chat -v does not restore it
- fix(api_server): _handle_responses drops text.format JSON schema — structured output constraints silently ignored
- state.db FTS corruption goes undetected — no integrity check, no repair path
- bug: fallback routing can select text-only models for image requests and hide the primary failure
- feat(kanban): persist worker session_id per run and pass --resume on respawn after unblock
- feat(kanban): support GitHub/OMO lifecycle bridge for Xiyou-style automation
- Expose update-safe TUI/composer hooks for voice transcript and composer events
- Hide or configure voice transcript status rows in editable dictation mode
- [Feature]: Per-Tool / Per-Toolset Approval Policies
- Context compression creates orphan sessions missing from state.db
- messaging platform
- feat: Add read-only / silent monitoring mode for WhatsApp adapter
- double-.hermes path mismatch, the HOME env var leak, and the fallback-notification UX problem
- Bug: Plattform-Bundle name `hermes-yuanbao` in `agent.disabled_toolsets` silently kills ALL tools in gateway path (Telegram + cron), CLI unaffected
- CLI /yolo (in-chat) does not bypass dangerous command approvals — env var freeze + missing enable_session_yolo call
- OpenAI Codex provider crashes with "'NoneType' object is not iterable" (HTTP None)
- DEEPSEEK_API_KEY blocked by env blocklist in gateway process — cron jobs fail with deepseek provider
- fix(feishu): Card action callback routing issues - invalid message_id and unrecognized /card command
- Discord plugin: profiles without explicit `discord:` block silently get `require_mention=true` + `auto_thread=true` (regression in cc8e5ec2a)
- [Bug]: DISCORD_ALLOWED_ROLES ignored by gateway _is_user_authorized — role-authorized users get 'Unauthorized user' rejection
- [Bug]: /new, /clear, and /reset commands freeze the terminal session
- openai-codex subscription backend returns HTTP 200 with response.output=None, causing Slack/cron failures
- RFC: Centralized Model/Provider Registry
- bug: openai-codex provider — TypeError: 'NoneType' object is not iterable on every request (gpt-5.5)
- [Feature]: Source-aware instruction gate — architectural mitigation for indirect prompt injection
- Named custom provider stale_timeout_seconds ignored because runtime provider is normalized to `custom`
- guard test (ignore)
- [Feature]: per-platform LLM request_overrides (extra_body / reasoning_effort / service_tier)
- One-shot smoke: add Flue-backed orchestration fixture
- Gateway should not treat stale Codex app-server progress as final response after post-tool silence
- `docker_run_as_host_user: true` breaks bundled skills: Hermes home is mounted into `/root/.hermes` but the container runs as a non-root user (`HOME=/home/pn`)
- [Bug]: gateway api_server streaming bypasses server-side tool-call loop when chat_template_kwargs.enable_thinking=false (model emits tool name as plain text)
- [Feature]: Pre-install python-telegram-bot in Umbrel Hermes Docker image
- YouTube Shorts filter not working in youtube-content skill
- v0.15.0 PyPI release breaks ALL platforms — plugin.yaml manifests missing from package
- RFC: On-demand tool/skill/MCP discovery — decouple schema registration from process lifecycle
- Pixshelf: local-first stock photo workflow command center
- [Bug]: baoyu infographic skill should not silently bypass image_generate
- Pixshelf v1.5: manual submission tracking for stock agencies
- `hermes config set` silently accepts unknown keys, writing them where the runtime never reads
- Honcho memory prefetch hang on fresh CLI subprocess in v0.15.0 (regression from #27190)
- [Bug] v0.15.0 Docker image: stage2-hook.sh, main-wrapper.sh missing; container_boot module removed
- Feature: Reduce cache-read token overhead for DeepSeek providers — configurable cache_ttl, skills snapshot trimming, memory compaction
- Windows: three bugs from daily use (plugin discovery, gateway exit code, Unicode decode
- holographic memory: HRR silently degrades to FTS5 when numpy is missing
- Make max_tokens configurable for aux vision calls
- Conversation compression desynchronizes session ID between agent context and gateway routing, causing silent message loss
- [Bug]: v0.15.0 Docker image:The TUI cannot be used in the dashboard.
- cron: skip_memory=True blocks fact_store/memory tools from all cron jobs
- TUI: Node.js OOM crash when agent uses browser tools repeatedly
- feat: model_profiles — per-model toolset and memory config
- Automatic background skill patching disrupts active sessions (severe impact on local models)
- ensure_hermes_home() creates root-owned dirs in profile subdirectories when kanban workers are dispatched
- Feature: opt-in webhook bypass for DISCORD_ALLOW_BOTS — allow operator-initiated probes without weakening bot-loop guard
- v0.15.0: Codex requests fail HTTP 400 when participant display_name contains non-ASCII (emoji breaks input[].name pattern)
- Architecture: State Persistence Precedence (Memory vs Skills vs Hooks)
- [Bug]: cronjob tool: create action always fails with "schedule is required for create" even when parameters are provided
- codex-oauth: 'NoneType' object is not iterable in _run_codex_stream (gpt-5.5) — every turn fails non-retryably
- Docs/Config: Plugin local scope enablement ambiguity
- [Bug]: CLI freezes after using /new command (WSL)
- Profile Codex auth can ignore global credential pool when local state is stale
- [workflow-engine] CRITICAL: variable substitution crashes on regex metachars in user input
- [workflow-engine] HIGH: loop and bash nodes leak subprocesses on timeout
- [workflow-engine] HIGH: README documents config env vars the engine never reads
- [workflow-engine] MEDIUM: workflow_run rate limit bypassable via concurrent calls (TOCTOU)
- [workflow-engine] chore: manifest gaps, side-effectful register(), dead code, unauth kanban dispatch
- [mcp_lazy] HIGH: synthetic mcp_server_<name> stub collides with a real MCP server named 'server'
- [mcp_lazy] HIGH: promote_server eager flag documented but never persisted
- [mcp_lazy] MEDIUM: _prev_mode dict leaks and goes stale; not cleared on session evict
- [mcp_lazy] MEDIUM: get_pool has unlocked check-then-set race on pool creation
- [mcp_lazy] MEDIUM: pre_tool_call gives no guidance for unpromoted server-stub calls
- [mcp_lazy] chore: undeclared pre_tool_call hook, nonexistent 'mcp_load_tools' name in docs, missing tests
- [a2a_fleet] CRITICAL: server never auto-starts — register() runs outside an event loop
- [a2a_fleet] CRITICAL: auth_required defaults to false on a cross-machine surface
- [a2a_fleet] HIGH: remove invented disable() hook — loader never calls it, port leaks on reload
- [a2a_fleet] HIGH: plugin.yaml missing kind / provides_tools / requires_env (token env undeclared)
- [a2a_fleet] MEDIUM: tighten wide-open CORS, anonymous /health peer leak, and peer-URL SSRF
- [a2a_fleet] MEDIUM: relocate tests to tests/plugins/ and cover sync-register + auth-default paths
- xai-oauth auxiliary client incorrectly uses Responses API (CodexAuxiliaryClient), causing 403 on compression/vision/web_extract
- [Bug]: Direct Copilot gpt-5.5 large resumes are killed by 12s Codex TTFB watchdog
- [Bug]: `hermes uninstall` does not work on Windows
- TUI: Thinking block leaks raw JSON and Σ character
- Hostinger VPS: migration Hermes Agent → Hermes WebUI impossible (tini + UID mismatch + sessions)
- /goal judge over-continues exploratory goals unless the assistant explicitly says the goal is complete
- /goal auto-continuation can be amplified by preflight compression/session split and resurrect stale task state
- Dashboard infinite reload loop in loopback mode — GET /api/auth/me returns 401 on every page load
- [Bug]: Provider/LLM switch leaves stale encrypted_content causing 400 errors on Telegram sessions
- [Bug]: Infinite reload loop / React state loop on Sessions tab (Firefox + Chrome) — repeated 401 on /api/auth/me (v0.15.0)
- show_reasoning should work independently of streaming in CLI mode
- Feature Request: Strip reasoning/<think> blocks from TTS preprocessing
- mcp add / mcp test raise NameError when mcp package not installed
- v0.14.0 dashboard breaks behind reverse proxies — two regressions
- Skills hub creates empty category directories when no skills installed
- [Bug]: Custom endpoint: ChatCompletions returns content, but Hermes treats response as empty (v0.14.0)
- fix: atomic_replace() fails with EXDEV when HERMES_HOME is a cross-filesystem symlink
- fix(gateway): Feishu session cancellation orphans session guard, permanently blocking messages
- Custom endpoint pricing can overestimate Crof qwen3.5-9b cost by 1,000,000x
- MCP OAuth callback: module-level port global causes port collisions and structural weaknesses vs upstream
- Bug: send_message tool bypasses validate_media_delivery_path security check
- Proposal: Add Mnemosyne to official memory provider documentation
- feat(swarm): support custom verifier/synthesizer body + skills
- Template conversion failed
- Error occurred in the operation of the agent node in the workflow.
- PubSub client overrides Sentinel client when REDIS_USE_SENTINEL is enabled
- Frontend description of the Retrieval node output does not match the actual output
- JSON type input var raise Intenal server error
- cannot extract elements from a scalar
- 负载均衡 为模型配置多组凭据，并自动调用，此功能无法选择
- 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