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
- [ROCm][Perf] Skip cleaning sparse prefill MQA logits
- [Core] shm tensor arena for efficient cpu->gpu worker broadcast
- [Bugfix][Kernel] Fix divergent warp collectives in partial NeoX QK-Norm+RoPE
- [ROCm][Kimi-K3] Enable opt-in K3 SiTUv2 A8W4 routed MoE
- [ROCm][AMD] Kimi-K3 Gap and Roadmap Tracking
- [Bugfix] Fix MiniMax M3 prompt reasoning initialization
- [Feature]: SM8x (Ampere A100/A800) support for DeepSeek-V4-Flash / DeepSeek-V4-Flash-0731 DSpark
- Add MoNe experts pruning support
- [Model] Apertus 1.5
- [Core][Distributed] Size custom all-reduce buffers at init so batch-invariant mode can use them
- Docs
- Python not yet supported