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] Use a large HTTP stream buffer in aiohttp to avoid ContentLengthError
- [Bugfix][Frontend] Normalize constrained Harmony recipients
- [Bug]: AssertionError: Encoder cache miss
- [Bugfix][Kernel] Zero-init Marlin GEMM output/reduce buffers for CUDA graph safety
- [Bug]: NotImplementedError: No NvFp4 MoE backend supports the deployment configuration.
- [Roadmap] Minimax M3
- [Bugfix] Deterministic MoE combine (reduce_scatterv) under VLLM_BATCH_INVARIANT
- Fix #40004: [Feature]: Priority scheduling supports preemption of requests in the
- [Misc] Add and enable Triton kernel unit tests on XPU
- [Model] Enable LoRA support for tower and connector in Voxtral
- Docs
- Python not yet supported