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
- [Perf][DSv4.1] Size the long-context prefill workspaces by what a chunk can use
- [Bugfix][MiniMax-M3] Keep video timestamps with the processor cache
- [Bugfix][MiniMax-M3] Cap video frames at the encoder's per-video budget
- Fix/multibackend preferred block size
- [Security] Validate NIXL peer topology before rank expansion
- [Perf][Core][Mamba] Export prefill checkpoints at or before the initial-state column
- [ROCm] MonoKernel for GLM 5.2
- [Bugfix] Dequantize DeepSeek-V4 wo_a for non-DeepGEMM linear backends
- [Bugfix][Attention] Use a block size only when every backend prefers it
- [Bug]: token_indices_to_sample underflows past the request's query start with PP > 1 spec decode
- Docs
- Python not yet supported