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
- [Bugfix][Model Runner] Bound dummy seq_lens by max_model_len
- [RFC]: Decouple draft-model parallelism from the target model (PCP/DCP + speculative decoding)
- [Performance]: Avoid scanning the full KV block table
- [RFC]: Allow the DSA Indexer to Use Context Parallelism Independently
- [Performance]: Add native layer-fused MoE parameter loading for weight reload
- [Bug]: Qwen3-Omni deepstack drops embedding modality after torch.split, breaking use_audio_in_video
- [CI] Fix nixl harness teardown: TERM grace before SIGKILL
- [RFC]: Progressive block handoff for NIXL Push
- [Bugfix][Tokenizer] Avoid retaining pool overflow copies
- [Bugfix][Model] Keep embedding modality through the Qwen3-Omni deepstack split
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