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]: finish_reason is "tool_calls" for a turn truncated at max_tokens, hiding the length stop from clients
- Revert "[Perf] Add fused DFlash2 grouped convolution (#55960)"
- [CI] Raise fault-detection deadline 45s -> 75s in FT E2E test
- [Bug]: CPU W4A16 Whisper fails: cpu_gemm_wna16 rejects 3-D encoder activations; packed k_proj bias is synthesized incorrectly
- [Installation]: v0.30.0 CPU wheels now require manylinux_2_39 (glibc 2.39), breaking installation on Ubuntu 22.04/Rhel9
- [Bugfix] Attach DeepSeek-V4 request tools to existing system/developer messages
- [RFC]: KVPP (KV pipeline parallel, LayerSplit) for vLLM
- [Bugfix] Avoid O(n) strip_covered_mm_data work per realtime step
- [Bug]: Qwen3.5/3.8 multimodal + native MTP crashes in profile_run — 'NoneType' object has no attribute 'size'
- Revert "[Bugfix][Model Runner V2] Route dummy tokens to MoE experts during profiling (#57270)"
- Docs
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