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
- [Bug]: V1 streaming-session rebuild leaves stale prefix-cache block hashes and can produce incorrect output
- [Perf] Add mm_tensor_ipc=cuda_ipc TP-aware GPU transport
- [Bug]: MTP speculative decoding is broken with pipeline parallelism (PP>1) — three distinct failures
- [Bug]: Token truncation leaves stale Request.block_hashes and can cause incorrect KV cache hits
- [Bugfix] Fix pipeline parallelism for Kimi-Linear
- [Bug]: Tools streaming internal error when `VLLM_ENFORCE_STRICT_TOOL_CALLING=false` and `tool_choice=required`
- [RFC]: ReplaySSM: cache SSM inputs instead of state for faster standard and speculative decode (Mamba2 + GDN)
- POST /wake_up fails with AttributeError: 'list' object has no attribute 'zero_' in init_fp8_kv_scales, wedging the engine (health stays green, completions hang)
- [Bug]: Decode instance segfaults on NIXL `loadRemoteMD` after prefill pod restarts in P/D disaggregation
- [Bugfix] Dispatch python builtin tool call in ParsableContext
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- Python not yet supported