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] compressed-tensors: allow format=dense sparsity_config to load
- [Bugfix] compressed-tensors: allow format=dense sparsity_config to load (backport #51189 to v0.24.0)
- [Bugfix] compressed-tensors: allow format=dense sparsity_config to load (backport #51189 to v0.26.0)
- fix: Skip empty DeepSeek-V4 FlashInfer attention slices
- [Bugfix][Sampler] Honor per-request seeds in partially-seeded CPU batches
- [Feature] IndexCache for DeepSeek-V4 (validated on V4-Flash-0731, including DSpark on to accelerate on top of
- [RFC]: Model Runner V2 Pluggable Design
- [Feature]: DeepSeek V4: option to preserve <think>/</think> markers in chat completion content
- [CI/Build]: source_file_dependencies still point at pre-libtorch_stable csrc paths, so kernel jobs no longer trigger
- [Bugfix][Core] Make EncoderDecoderCacheManager slot release idempotent
- Docs
- Python not yet supported