vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- fix: require a real exit code before treating engine liveness monitors as dead
- [Bug]: AsyncLLM streaming session appends later chunk tokens to the caller's prompt list in place
- [Bugfix][Spec Decode] Profile adaptive verification tails as mixed batches
- [Bug]: installed-but-unloadable torchcodec breaks video requests — OSError escapes the guards, and check_torchcodec_available() can only raise
- [Bugfix] Eliminate frontend ZMQ port TOCTOU with inherited listeners
- [Bug]: Evaluating GLM-5.1-FP8 for reasoning over large contexts produces unexpectedly poor level of accuracy.
- [Bug]: DeepGEMM is reported supported on sm_121 (GB10) but faults — support_deep_gemm() accepts the whole 120 capability family
- [Kimi-K3] AG-GEMM for Sequence Parallelism
- [Spec Decode] Support sample_from_anchor for DFlash draft models
- [Bug] Qwen3.8-Flash-Next: CUBLAS_STATUS_INTERNAL_ERROR / illegal memory access in GDN path with prefix caching on GB10 (sm_121); --no-async-scheduling does not help
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- Python not yet supported