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
- [Model][Quant] compressed-tensors WNA16 input embeddings + tied embedding (lm_head) support
- Fix cp_gather_cache block table bounds
- Fix moe_wna16 sorted token bounds
- [Bugfix] Fix SamplingParams repr, docstrings, top_k validation order, and convert StructuredOutputsParams to msgspec.Struct
- Fix gpt-oss required tool choice constraints
- Fix LMCache MP LoRA cache salt keying
- [Core] Priority-based preemption at max_num_seqs
- [ROCm][Kernel] Extend skinny gemm N=5 to N=8 cases on GFX12 (RDNA4) using SWMMAC optimization
- [Core] Priority scheduling: preempt running requests for higher-priority waiting requests at max_num_seqs
- [Bugfix][Frontend] Handle constrained Harmony output without recipient
- Docs
- Python not yet supported