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
- [Test] Make the determinism tests runnable for MLA models
- [Test] Compare NVFP4 batch-invariance logprobs bitwise
- [EPLB] Make migration peer limit configurable
- [Bug]: V2 rejection_sample drops target tokens with ids >= draft vocab width (probabilistic drafts from a narrower draft head)
- [Bug]: V1 rejection sampler reads draft_probs with the target's vocab width when the draft head is narrower (out-of-bounds reads, stray token ids)
- [Bug]: thinking_token_budget forces a second </think> when the natural </think> is inside accepted drafts (spec decode, V1 runner)
- [ROCm][Perf][MiniMax-M3] Defer the FFN all-reduce into the next layer's norm
- [KV Connector][NIXL] Transfer DeepSeek-V4.1 packed MLA rows whole
- [Bugfix] Preserve empty tensor metadata in packed IPC
- [Bugfix] Reject dynamic speculative decoding with ngram_gpu
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