vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
Triage Issues!
When you volunteer to triage issues, you'll receive an email each day with a link to an open issue that needs help in this project. You'll also receive instructions on how to triage issues.
Triage Docs!
Receive a documented method or class from your favorite GitHub repos in your inbox every day. If you're really pro, receive undocumented methods or classes and supercharge your commit history.
Python not yet supported51 Subscribers
View all SubscribersAdd a CodeTriage badge to vllm
Help out
- Issues
- [RFC]: Complete Model Runner V2 pipeline parallelism: scheduling, speculative decoding, and PP-first DP/EP topology
- fix: release committed encoder data for resumable sessions
- fix: don't ship uninitialized prompt logprobs after remote prefill
- [Docs] Add a readiness checklist for new tool-calling models
- [Bug]: Gemma4 tool parser (non-streaming): finish_reason=tool_calls with empty tool_calls array — model's move silently lost under concurrent load
- [Bugfix] Include disabled multimodal modalities in the model config hash (#50891)
- [Bugfix] Validate Kimi attention layer configuration
- [Bugfix] Enhance reasoning extraction to handle prefixes and missing …
- [Bugfix][Model] Kimi K3: pad the MoE intermediate by the effective shard count, on both backends
- [Bug]: Text emitted before the reasoning start tag escapes both the gemma4 parser and structured output, breaking json_schema responses
- Docs
- Python not yet supported