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][DeepseekV4] Harden compress_ratio fallback for transformers >=4.57
- [Bugfix] Make openai_serving_render optional in OpenAIServingChat and OpenAIServingCompletion
- [deepseek_v4] Route top-level head.weight + embed.weight to MTP shared_head/embed_tokens
- Enable FlashInfer checkpointing SSU STP no-fallback path
- [Core] Add prefix-cache-aware routing for internal DP load balancing
- [RFC] NSA is architecturally incompatible with NVIDIA consumer/workstation GPUs — MLA is the only viable sparse attention path
- [Usage]: Support Gemma 4 E4B, 31B, 26B-A4B, and assistant variants (MTP) on TPU v6e 1x1 with vLLM
- [Bug]: `vllm serve --config=...` accepts the config path but does not expand the YAML
- [Perf][Core] Use power-of-two-choices for DP engine selection at large DP
- [Hybrid SSM] Investigate accuracy divergence between `mamba_chunk_scan` and `selective_state_update` kernels
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