vllm - ✅(Solved) Fix [Bug]: Inaccurate available memory for KV cache when sleep mode is enabled likely due to custom allocators [1 pull requests, 1 participants]
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vllm-project/vllm#40256•Fetched 2026-04-19 15:04:43
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djparenteError Message
Estimated available memory for the KV cache differs 1.99 GiB when --enable-sleep-mode is set (5.16 GiB) as compare to unset (3.17 GiB)
Root Cause
Reproduction steps
- Install/configure vllm (e.g., from commit bfde49e28)
- Run the launch script below (on a dual-4090 system; may need to adapt the script to a single GPU, and, if so, use a smaller model that will fit in VRAM)
- Observe out of memory error occurs and that launch reports "Available KV cache memory: 5.16 GiB" prior to crash" (This estimate is incorrect and the root cause of the crash.)
- Run the same launch script without
--enable-sleep-mode - Observe it loads correctly and that launch reports "Available KV cache memory: 3.17 GiB" (this is correct).
Fix Action
Fix / Workaround
============================== CPU Info
Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 28 On-line CPU(s) list: 0-27 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-14700K CPU family: 6 Model: 183 Thread(s) per core: 2 Core(s) per socket: 20 Socket(s): 1 Stepping: 1 CPU(s) scaling MHz: 46% CPU max MHz: 5600.0000 CPU min MHz: 800.0000 BogoMIPS: 6835.20 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr ibt flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 768 KiB (20 instances) L1i cache: 1 MiB (20 instances) L2 cache: 28 MiB (11 instances) L3 cache: 33 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-27 Vulnerability Gather data sampling: Not affected Vulnerability Ghostwrite: Not affected Vulnerability Indirect target selection: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Old microcode: Not affected Vulnerability Reg file data sampling: Mitigation; Clear Register File Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsa: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
PR fix notes
PR #40258: [Bugfix] Corrects estimate of torch memory use causing OOM due to incorrect KV cache space estimation when sleep mode on (Fixes #40256)
- Repository: vllm-project/vllm
- Author: djparente
- State: open | merged: False
- Link: https://github.com/vllm-project/vllm/pull/40258
Description (problem / solution / changelog)
[Bugfix] Correct torch memory measurement during profiling that was invalid when custom allocators were used.
Co-authored-by: GitHub Copilot Co-authored-by: ChatGPT 5.4 Thinking Co-authored-by: ChatGPT 5.4 Pro Co-authored-by: Claude Opus 4.6 Co-authored-by: Claude Opus 4.7
Purpose
This PR repairs an erroneous memory estimation that arises during profiling when custom CUDA allocators are in use (e.g., sleep mode). This Fixes
To calculate how much memory is available for the KV cache vLLM profiles memory usage (gpu_worker.py calling mem_utils.py's measure() function).
The strategy vllm has been using is outlined in MemoryShapshot.measure(), which profiles the memory usage in terms of torch-related memory and non-torch memory. (This is because it also needs to keep track of peak torch memory, which may be transiently higher during the forward pass of a model).
The strategy vllm had been using is to measure torch memory using torch.accelerator.memory.memory_reserved. However, there were changes accepted to enable sleep mode recently. To support sleep mode, this uses a custom CUDA allocator that allows vllm to selectively discard some parts of GPU memory during sleep.
Unfortunately, when custom allocators are used, this causes the measure() method to over-estimate torch memory use. This is because torch.accelerator.memory.memory_reserved becomes an unreliable estimate of torch-related memory once custom allocaters are being used.
In some cases, this estimate can exceed all CUDA memory use, causing measure() to incorrectly report that non-torch memory is negative. This is obviously incorrect and can lead to out of memory errors because vllm believes it has more memory to allocate to the KV cache than is truly available.
More details are shown in a related bug.
This PR makes one surgical change to the measure function, replacing the estimate of torch memory with
stats.get("allocated_bytes.all.current", 0)Where stats is:
stats = torch.accelerator.memory_stats(device)The problem can be illustrated by observing the intermediate variables in measure() on one CUDA device during
| Measurement | Sleep off old code | Sleep on old code |
|---|---|---|
| Torch Peak | 19.73 | 19.73 |
| Total memory | 23.52 | 23.52 |
| Free memory | 3.98 | 4.02 |
| Cuda memory | 19.54 | 19.5 |
| Torch memory (old: memory_reserved) | 18.92 | 20.87 ← |
| Torch memory (new: allocated_bytes.all.current) | 18.71 | 18.71 |
| Non-torch memory | 0.62 | -1.36 ← |
A table in testing results, below, shows the correction of this problem with the proposed code change.
Test Plan
I observed the measured memory calculated in the mem_utils.py MemoryShapshot.measure() function using the old calculation method (memory_reserved()) and then new method stats.get("allocated_bytes.all.peak", 0). Results from a load of quantized Llama 70B on a 2x 4090 system are shown in the table (test result). Arrows and bold indicates the erroneous quantities using the memory_reserve
The command used to run was:
VLLM_SERVER_DEV_MODE=1 python -m vllm.entrypoints.openai.api_server \
--model hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 \
--tensor-parallel-size 2 \
--dtype half \
--quantization awq_marlin \
--kv-cache-dtype fp8 \
--max-model-len 36000 \
--max-num-seqs 1 \
--gpu-memory-utilization 0.97 \
--host 0.0.0.0 \
--port 5555 \
--enable-chunked-prefill --max-num-batched-tokens 8192 \
--enforce-eager \
--enable-sleep-modeFor the no sleep tests, the --enable-sleep-mode flag was disabled.
Test Result
The table below shows intermediate calculations in MemorySnapshot.measure() when sleep (and therefore custom allocators) are on/off and in the old code as compared to the new code. When sleep is on, memory_reserved reports more memory use by torch than is being used in total by CUDA, which is not a correct estimate of the torch memory use (bolded cells with arrows). This leads to non-torch memory being estimated to be negataive. The downstream result of this
| Sleep off | Sleep off | Sleep on | Sleep on | |
|---|---|---|---|---|
| Measurement (GiB) | Old code | New code | Old code | New code |
| Torch Peak | 19.73 | 19.73 | 19.73 | 19.73 |
| Total memory | 23.52 | 23.52 | 23.52 | 23.52 |
| Free memory | 3.98 | 3.98 | 4.02 | 4.02 |
| Cuda memory | 19.54 | 19.54 | 19.5 | 19.5 |
| Torch memory (old: memory_reserved) | 18.92 | 18.92 | 20.87 ← | 20.87 ← |
| Torch memory (new: bytes_allocated) | 18.71 | 18.71 | 18.71 | 18.71 |
| Non-torch memory | 0.62 | 0.83 | -1.36 ← | 0.79 |
On the testing machine sleep on / old code lead to OOM because vllm overestimates how much space it can allocate to the KV cache, whereas sleep on / new code resolves the OOM.
Additionally, we can directly observe the KV cache estimates:
| Sleep off | Sleep off | Sleep on | Sleep on | |
|---|---|---|---|---|
| Measurement (GiB) | Old code | New code | Old code | New code |
| Estimate Available KV Cache | 3.17 | 2.96 | 5.16 ← Wrong | 3.0 |
This the correction prevents discordance in the estimated available KV cache when sleep mode is enabled as compared to disabled, as expected by issue #40256.
Contact
Please do not hesitant to contact me about remaining issues with this PR. Thank you for considering this change.
AI Contributors
I consulted extensively with Github Copilot, ChatGPT Thinking/Pro, Claude 4.6/4.7 to understand the codebase and discuss possible solutions. I considered at length these recommendations, explored possible solutions myself, and personally verified the solution arrived at and proposed in this PR. I take responsibility for its proposal.
<details> <summary> Essential Elements of an Effective PR Description Checklist </summary>
- The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
- The test plan, such as providing test command.
- The test results, such as pasting the results comparison before and after, or e2e results
- (Optional) The necessary documentation update, such as updating
supported_models.mdandexamplesfor a new model.
Changed files
vllm/utils/mem_utils.py(modified, +13/-7)
Code Example
==============================
System Info
==============================
OS : Ubuntu 24.04.4 LTS (x86_64)
GCC version : (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
Clang version : Could not collect
CMake version : version 3.28.3
Libc version : glibc-2.39
==============================
PyTorch Info
==============================
PyTorch version : 2.11.0+cu130
Is debug build : False
CUDA used to build PyTorch : 13.0
ROCM used to build PyTorch : N/A
XPU used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.13 (main, Apr 7 2026, 20:45:25) [Clang 22.1.1 ] (64-bit runtime)
Python platform : Linux-6.17.0-20-generic-x86_64-with-glibc2.39
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : Could not collect
CUDA_MODULE_LOADING set to :
GPU models and configuration :
GPU 0: NVIDIA GeForce RTX 4090
GPU 1: NVIDIA GeForce RTX 4090
Nvidia driver version : 590.48.01
cuDNN version : Could not collect
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 28
On-line CPU(s) list: 0-27
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i7-14700K
CPU family: 6
Model: 183
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 1
Stepping: 1
CPU(s) scaling MHz: 46%
CPU max MHz: 5600.0000
CPU min MHz: 800.0000
BogoMIPS: 6835.20
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr ibt flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 768 KiB (20 instances)
L1i cache: 1 MiB (20 instances)
L2 cache: 28 MiB (11 instances)
L3 cache: 33 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-27
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Old microcode: Not affected
Vulnerability Reg file data sampling: Mitigation; Clear Register File
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.7
[pip3] numpy==2.2.6
[pip3] nvidia-cublas==13.1.0.3
[pip3] nvidia-cuda-cupti==13.0.85
[pip3] nvidia-cuda-nvrtc==13.0.88
[pip3] nvidia-cuda-runtime==13.0.96
[pip3] nvidia-cudnn-cu13==9.19.0.56
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft==12.0.0.61
[pip3] nvidia-cufile==1.15.1.6
[pip3] nvidia-curand==10.4.0.35
[pip3] nvidia-cusolver==12.0.4.66
[pip3] nvidia-cusparse==12.6.3.3
[pip3] nvidia-cusparselt-cu13==0.8.0
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu13==2.28.9
[pip3] nvidia-nvjitlink==13.0.88
[pip3] nvidia-nvshmem-cu13==3.4.5
[pip3] nvidia-nvtx==13.0.85
[pip3] pyzmq==27.1.0
[pip3] torch==2.11.0
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0
[pip3] torchvision==0.26.0
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.19.1rc1.dev309+gf2145efcb (git sha: f2145efcb)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
GPU0 GPU1 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PHB 0-27 0 N/A
GPU1 PHB X 0-27 0 N/A
Legend:
X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks
==============================
Environment Variables
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_dan
---
VLLM_SERVER_DEV_MODE=1 python -m vllm.entrypoints.openai.api_server \
--model hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 \
--tensor-parallel-size 2 \
--dtype half \
--quantization awq_marlin \
--kv-cache-dtype fp8 \
--max-model-len 36000 \
--max-num-seqs 1 \
--gpu-memory-utilization 0.97 \
--host 0.0.0.0 \
--port 5555 \
--enable-chunked-prefill --max-num-batched-tokens 8192 \
--enforce-eager \
--enable-sleep-mode
---
stats.get("allocated_bytes.all.current", 0)
---
stats = torch.accelerator.memory_stats(device)RAW_BUFFERClick to expand / collapse
Your current environment
<details> <summary>The output of <code>python collect_env.py</code></summary>==============================
System Info
==============================
OS : Ubuntu 24.04.4 LTS (x86_64)
GCC version : (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
Clang version : Could not collect
CMake version : version 3.28.3
Libc version : glibc-2.39
==============================
PyTorch Info
==============================
PyTorch version : 2.11.0+cu130
Is debug build : False
CUDA used to build PyTorch : 13.0
ROCM used to build PyTorch : N/A
XPU used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.13 (main, Apr 7 2026, 20:45:25) [Clang 22.1.1 ] (64-bit runtime)
Python platform : Linux-6.17.0-20-generic-x86_64-with-glibc2.39
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : Could not collect
CUDA_MODULE_LOADING set to :
GPU models and configuration :
GPU 0: NVIDIA GeForce RTX 4090
GPU 1: NVIDIA GeForce RTX 4090
Nvidia driver version : 590.48.01
cuDNN version : Could not collect
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 28
On-line CPU(s) list: 0-27
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i7-14700K
CPU family: 6
Model: 183
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 1
Stepping: 1
CPU(s) scaling MHz: 46%
CPU max MHz: 5600.0000
CPU min MHz: 800.0000
BogoMIPS: 6835.20
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr ibt flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 768 KiB (20 instances)
L1i cache: 1 MiB (20 instances)
L2 cache: 28 MiB (11 instances)
L3 cache: 33 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-27
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Old microcode: Not affected
Vulnerability Reg file data sampling: Mitigation; Clear Register File
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace
==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.7
[pip3] numpy==2.2.6
[pip3] nvidia-cublas==13.1.0.3
[pip3] nvidia-cuda-cupti==13.0.85
[pip3] nvidia-cuda-nvrtc==13.0.88
[pip3] nvidia-cuda-runtime==13.0.96
[pip3] nvidia-cudnn-cu13==9.19.0.56
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft==12.0.0.61
[pip3] nvidia-cufile==1.15.1.6
[pip3] nvidia-curand==10.4.0.35
[pip3] nvidia-cusolver==12.0.4.66
[pip3] nvidia-cusparse==12.6.3.3
[pip3] nvidia-cusparselt-cu13==0.8.0
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu13==2.28.9
[pip3] nvidia-nvjitlink==13.0.88
[pip3] nvidia-nvshmem-cu13==3.4.5
[pip3] nvidia-nvtx==13.0.85
[pip3] pyzmq==27.1.0
[pip3] torch==2.11.0
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0
[pip3] torchvision==0.26.0
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.19.1rc1.dev309+gf2145efcb (git sha: f2145efcb)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
GPU0 GPU1 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PHB 0-27 0 N/A
GPU1 PHB X 0-27 0 N/A
Legend:
X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks
==============================
Environment Variables
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_dan🐛 Describe the bug
Key Problem
When sleep mode is enabled (and therefore custom CUDA allocators become part of the memory storage pathway), VLLM incorrectly estimates the amount of memory available for the KV cache and this can lead to OOM.
Reproduction steps
- Install/configure vllm (e.g., from commit bfde49e28)
- Run the launch script below (on a dual-4090 system; may need to adapt the script to a single GPU, and, if so, use a smaller model that will fit in VRAM)
- Observe out of memory error occurs and that launch reports "Available KV cache memory: 5.16 GiB" prior to crash" (This estimate is incorrect and the root cause of the crash.)
- Run the same launch script without
--enable-sleep-mode - Observe it loads correctly and that launch reports "Available KV cache memory: 3.17 GiB" (this is correct).
Launch script:
VLLM_SERVER_DEV_MODE=1 python -m vllm.entrypoints.openai.api_server \
--model hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4 \
--tensor-parallel-size 2 \
--dtype half \
--quantization awq_marlin \
--kv-cache-dtype fp8 \
--max-model-len 36000 \
--max-num-seqs 1 \
--gpu-memory-utilization 0.97 \
--host 0.0.0.0 \
--port 5555 \
--enable-chunked-prefill --max-num-batched-tokens 8192 \
--enforce-eager \
--enable-sleep-modeObserved behavior
Estimated available memory for the KV cache differs 1.99 GiB when --enable-sleep-mode is set (5.16 GiB) as compare to unset (3.17 GiB)
Expected behavior
Estimated available memory for the KV cache should be very similar (although perhaps not completely identical) when --enable-sleep-mode is set or unset.
Underlying error and possible solution
To calculate how much memory is available for the KV cache vLLM profiles memory usage (gpu_worker.py calling mem_utils.py's measure() function).
The strategy vllm has been using is outlined in MemoryShapshot.measure(), which profiles the memory usage in terms of torch-related memory and non-torch memory. (This is because it also needs to keep track of peak torch memory, which may be transiently higher during the forward pass of a model).
The strategy vllm had been using is to measure torch memory using torch.accelerator.memory.memory_reserved. However, there were changes accepted to enable sleep mode recently. To support sleep mode, this uses a custom CUDA allocator that allows vllm to selectively discard some parts of GPU memory during sleep.
Unfortunately, when custom allocators are used, this causes the measure() method to over-estimate torch memory use. This is because torch.accelerator.memory.memory_reserved becomes an unreliable estimate of torch-related memory once custom allocaters are being used.
In some cases, this estimate can exceed all CUDA memory use, causing measure() to incorrectly report that non-torch memory is negative. This is obviously incorrect and can lead to out of memory errors because vllm believes it has more memory to allocate to the KV cache than is truly available.
I think this can be remedied by changing, within MemoryShapshot.measure() the estimate of torch memory to be given by:
stats.get("allocated_bytes.all.current", 0)Where stats is:
stats = torch.accelerator.memory_stats(device)The problem can be illustrated by observing the intermediate variables in measure() on one CUDA device during
| Measurement | Sleep off old code | Sleep on old code |
|---|---|---|
| Torch Peak | 19.73 | 19.73 |
| Total memory | 23.52 | 23.52 |
| Free memory | 3.98 | 4.02 |
| Cuda memory | 19.54 | 19.5 |
| Torch memory (old: memory_reserved) | 18.92 | 20.87 ← |
| Torch memory (new: allocated_bytes.all.current) | 18.71 | 18.71 |
| Non-torch memory | 0.62 | -1.36 ← |
Implementing this fix leads to the following result:
| Sleep off | Sleep off | Sleep on | Sleep on | |
|---|---|---|---|---|
| Measurement (GiB) | Old code | New code | Old code | New code |
| Torch Peak | 19.73 | 19.73 | 19.73 | 19.73 |
| Total memory | 23.52 | 23.52 | 23.52 | 23.52 |
| Free memory | 3.98 | 3.98 | 4.02 | 4.02 |
| Cuda memory | 19.54 | 19.54 | 19.5 | 19.5 |
| Torch memory (old: memory_reserved) | 18.92 | 18.92 | 20.87 ← | 20.87 ← |
| Torch memory (new: bytes_allocated) | 18.71 | 18.71 | 18.71 | 18.71 |
| Non-torch memory | 0.62 | 0.83 | -1.36 ← | 0.79 |
I will file a PR proposing this change shortly.
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extent analysis
TL;DR
The most likely fix for the incorrect memory estimation issue when sleep mode is enabled is to update the MemoryShapshot.measure() method to use torch.accelerator.memory_stats(device).get("allocated_bytes.all.current", 0) instead of torch.accelerator.memory.memory_reserved to estimate torch memory usage.
Guidance
- Identify the
MemoryShapshot.measure()method in the vLLM codebase and update the torch memory estimation to usetorch.accelerator.memory_stats(device).get("allocated_bytes.all.current", 0). - Verify that the updated method correctly estimates the available memory for the KV cache when sleep mode is enabled.
- Test the updated code with the provided launch script to ensure that the out of memory error is resolved.
- Review the documentation and code comments to ensure that the update is properly documented and easy to understand.
Example
The updated MemoryShapshot.measure() method could look like this:
stats = torch.accelerator.memory_stats(device)
torch_memory = stats.get("allocated_bytes.all.current", 0)Replace the existing torch memory estimation with this updated code.
Notes
This fix assumes that the torch.accelerator.memory_stats(device).get("allocated_bytes.all.current", 0) method provides an accurate estimate of torch memory usage. If this is not the case, further investigation may be needed to determine the correct method for estimating torch memory usage.
Recommendation
Apply the workaround by updating the MemoryShapshot.measure() method to use the new torch memory estimation method. This should resolve the out of memory error and provide a more accurate estimate of available memory for the KV cache.
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FAQ
Expected behavior
Estimated available memory for the KV cache should be very similar (although perhaps not completely identical) when --enable-sleep-mode is set or unset.
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×6Another batch ranked right after the header list — different links, same matching logic.
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- [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