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
- [Core][Metrics] Collect iteration details during scheduling
- [Bug]: Chat Completions returns `annotations: null` (typed as one Annotation, not a list) and `usage.prompt_tokens_details: null`; strict OpenAI-schema validators reject both
- [ROCm][Perf] Fuse GDN decode (conv1d + delta rule + gated norm) into AITER's gluon kernel (Qwen3.8-27B)
- [Bugfix] Support strided weights in sharded state saving
- [ROCm][Spec Decode] Rank unified attention above ROCM_ATTN for spec decode and hybrid models
- [Perf][Spec Decode] Defer GDN spec decode state stores to the next step
- [Kernel] Add FlashInfer GDN and KDA prefill backend selection
- [Spec Decode] Add draft_context_window to bound DFlash/DSpark draft attention
- [ROCm][Perf] Batch short TurboQuant verify blocks and enable split-KV
- [ROCm][AMD] Generalize MiniMax-M3 mono decode architecture for TP=2, TP=4, and TP=8 on gfx950
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