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]: vLLM inference produces garbled output on long context for SFT'd Qwen3-14B (short context is normal)
- Support SentenceTransformer Dense projection layers for embedding models (stella_en_1.5B_v5)
- fix(tool-parser): stop converting "none" strings to Python None in minimax_m2 parser
- [Bug]: KV Cache Read/Write Index Corruption Under Concurrent Prefill of Variable-Length Sequences (vLLM V1, FlashInfer)
- [Feature][Performance]: Kimi K2.5: 2.4x tokenization overhead from slow HF pipeline
- [Bug]: Gemma 4 26B MoE NVFP4 fails under tensor-parallel-size 2 across all available MoE backends
- fix(reasoning): translate reasoning_effort in nemotron_v3 parser
- [BugFix] Fix streaming tool call empty fields with MTP: Pydantic null serialization + qwen3coder early return
- fix(tool-parser): preserve "none"/"nil" strings as valid enum values in minimax_m2
- [Bugfix] Fix glm4_moe_tool_parser._is_string_type for /v1/responses FunctionTool format
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