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]: quantization="mxfp8" + moe_backend="humming" crashes weight conversion with a bare KeyError: 'weight_scale' — the MXFP8 oracle selects humming, then a third-party schema converter raises
- [Bugfix][Offload] Preserve CPU residency for renamed NVFP4 expert weights
- [Kernel][Perf] Add H20 block-FP8 fused MoE config for E=512,N=128 (Qwen3.5-397B-A17B-FP8 TP8, up to 2.0x)
- [Security] Reject unresolved multimodal inputs before execution
- [Spec Decode] Fix adaptive verification startup on FA2 GPUs
- [Bugfix] Reject shape mismatches in ShardedStateLoader instead of partially loading (fixes #61681 mechanism)
- fix: validate ngram_gpu compatibility with disabled compilation
- [Bugfix][Core] Emit full reuse events for converged hybrid connector hits
- [Bugfix][KV Offload] Deduplicate replicated GQA heads in canonical storage
- [Feature][KV Offload] Enable canonical offload for chunked-local attention
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- Python not yet supported