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][MiMo] Apply vision attention sinks in the window attention path
- kernels: fused silu_and_mul + dynamic per-token FP8 quantization
- [Bugfix] Pick a KV block size supported by every attention backend
- [FEAT] Support fast engine recovery through weight cache
- [Bug] DeepSeek-V4 on SM12x: NaN MQA logits drive top_k_per_row_prefill to emit uninitialized smem as indices -> illegal memory access
- [Bug]: [Regression] Assertion res == CUresult::CUDA_SUCCESS failed in FlashMLA (phase1.cuh) for DeepSeek-V4 on v0.26.0 (Works in v0.25.0)
- [ROCm][Perf] Speed up single-group MoE routing
- [Model] Enable batch-invariant mixed decode and prefill for Qwen GDN
- [Model Loader] Introduce custom weight copy
- Fix DoS via sample-rate forgery bypassing audio decode duration guard
- Docs
- Python not yet supported