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
- [Model Validation] SmolLM2-360M-Instruct batch invariance
- [Bugfix] Track token usage for ParsableContext
- [Docs] Validate SmolLM2 batch invariance
- [Bug]: poolside_v1 reports zero Responses reasoning_tokens for prompt-opened thinking spans
- [Bug]: Responses silently ignores named tool_choice for unsupported XML tool parsers
- [Rust Frontend] Add poolside_v1 reasoning parser
- [Bug]: int8_per_token_head KV cache corrupts Gemma-4 (hybrid attention) output under load on Triton
- [Bug]: Gemma4 streaming: `content` comes back completely empty while `reasoning` holds the model's entire output when the reasoning channel is left open
- [Attention] Add FlashInfer XQA decode support on SM12x
- [Fix] Strip whitespace for VLLM_USE_MODELSCOPE env check
- Docs
- Python not yet supported