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][collect-env] Report the cuDNN runtime version
- [Perf] Tune GLM-5.3-Flash block-FP8 MoE for H20
- [feat] Introduce platform-owned RoPE implementations
- [RFC]: Meta-device operator capture: see which operators a model runs on this platform, without weights or device memory
- [Kernel] Register the cudnn backend for FlashInfer BF16 mm
- Fix Mooncake state cleanup for re-admitted requests
- [RFC]: DeepSeek-V4.1-Flash performance on MI325X (gfx942)
- [Bug]: validate_xgrammar_grammar skips unsupported-feature checks for JSON schemas nested in structural tags
- [Feature][Profiler] Meta-device operator capture
- [ROCm][Perf] Fold Q fp8 quantization into QkNormRopeKvCacheFusionPass (drop per-layer scaled_quant)
- Docs
- Python not yet supported