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]: Duplicate registration of a fake implementation for the gptq_marlin_repack operator causing vllm serve to fail.
- [Bug]: FP8 KV Cache fails for google/gemma-3-1b-it on Hopper with backend FlashInfer
- [Bug]: "expandable_segments: True" causes vLLM EngineCore initialization to fail when running Qwen3 VL models
- [Bug]: "\n\n" content between reasoning and tool_call content when tool_call and stream mode
- [Feature]: Add P/D disaggregation deployment on Ray
- FlashInfer-Bench Integration for vLLM
- [Bug]: GLM-4.5 reasoning parser streaming fails without tools in request - missing as_list() conversion
- [Feature]: Model Generation Monitoring and Intervention (including 1. request-level thinking budget control as supported in Qwen/Claude APIs 2. repetition detection and truncation)
- [Bug]: vllm with lmcache crashes on semi-large number of parallel queries
- [Model loading error]: quantized version of Llama-3.2-11B-Vision-Instruct
- Docs
- Python not yet supported