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]: xlam and hunyuan_a13b tool parsers drop the arguments of any tool call that follows an empty-argument call (streaming)
- [Bug]: A tool call truncated by max_tokens diverges between streaming and non-streaming, and leaks raw <tool_call> markup into content (non-streaming)
- [Bugfix] Fix Gemma4 engine parser returning bare values as strings
- [Bugfix][Responses API] Keep streamed function call IDs in completed responses
- [Tests][Spec Decode] Add gemma4 MTP acceptance rates test
- [Feature]: Deduplicate replicated MLA KV across TP ranks in native offloading
- [Bug]: DFlash/DSpark draft acceptance collapses with automatic prefix caching enabled
- [Bugfix][Frontend] Preserve abort finish_reason for scale-out token streams
- [GLM 5.2] Integrate NVFP4 MegaMoE
- [MoE] Add flashinfer.moe_ep (NCCL-EP) all2all backends: flashinfer_ep_low_latency / flashinfer_ep_high_throughput
- Docs
- Python not yet supported