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]: speculative_config.method="ngram_gpu" with compilation_config.mode="NONE" kills engine init — ValueError: No compilation mode is set.
- [Bugfix] Exclude cudagraph padding rows from the per-tensor FP8 MoE amax
- [Bugfix][Multimodal] Auto derive max_num_batched_tokens from max_model_len and max_num_seqs
- [Doc] Fix NGINX load balancer config: fail_timeout, streaming and keep-alive
- [Bug]: NixlConnector P/D: pulls and deferred notifications against TTL-evicted remote agents block 60s per call in libfabric connect(), starving DP engines to death
- [CI][AMD] Add queue fallback config for AMD GPU queues
- [RFC]: PD disaggregation + RL lifecycle (pause, sleep, abort) tracking
- [Bugfix] Fix M-RoPE positions stride assertion in compile_sizes graphs
- [Bug]: Mamba2 hybrid models crash once the prompt is longer than block_size (regression from #57329)
- [Bug]: sharded_state can't round-trip models with attention/KV-cache scale params (Missing keys ...attn.q_scale, k_scale, v_scale, prob_scale)
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