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] Couple audio+video in mm processor cache for use_audio_in_video (fixes #44538)
- [ROCm][MLA] AITER FP8 ASM prefill backend
- [Bug]: GLM-5 FP8 OOM for long inputs at `flash_mla_cuda.sparse_decode_fwd` on H200
- [Feature] Add fault tolerance framework (simplified) for DP+EP external LB deployments
- [Feature][ROCm]: Add env-var gates for F2 (fused RMSNorm+MXFP4-quant) and F3 (fused RoPE+MLA KV-cache) in DeepSeek-V3 MXFP4 uplift
- [4/N][KV-Cache Layout Refactor] Standardize KV cache layout
- [Refactor] RDNA3 W4A16 MoE dispatch to oracle/expert class pattern
- [Bugfix][Voxtral Realtime] Fix token feedback timeout silent hang
- [Bugfix] RayExecutorV2: Defer `vllm_config` deserialization until after `CUDA_VISIBLE_DEVICES` is set
- [Feature][Frontend] Add prefix cache hit rate to usage details
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