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
- [Bug]:
- [Feature]: Upstream DGX spark improvements from Avarok-Cybersecurity/dgx-vllm
- [Bug]: vLLM crashed with V100 by running zai-org/GLM-OCR
- [Feature] Fuse per-group FP8 dynamic quant onto Triton attention kernel
- [Bug]: AssertionError in cutlass_scaled_mm during profile_run for FP8 pooling/reranker models
- [Bug]: The 2-bit model repeatedly outputs !!!!, while Transformers works correctly.
- [Bug]: Benchmark tuning MoE kernel config fails due to triton 3.6
- [LoRA] Add LoRA support for Qwen3OmniMoeThinkerForConditionalGeneration
- [Performance]: KV cache ~7x memory overestimation for hybrid Mamba/attention models (Qwen3.5)
- [Bugfix] Fix TOCTOU race in KV block allocator causing prefix-cache block theft
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- Python not yet supported