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
- docs: add AI Badgr hosted GPU deployment option
- [Model Runner V2][Spec Decode]Support peagle spec decode
- [Bug]: Setting prompt_embeds does not work for vision-language models
- [Bug]: [Bug] CUDA illegal memory access with Gemma-4-31B-it + RedHatAI/gemma-4-31B-it-speculator.dflash (DFlash)
- feat: add optional torchembed RoPE backend
- Fix cumem allocator cleanup on allocation failures
- [Bugfix][Model] GraniteMoE: load FP8_DYNAMIC expert weight_scale tensors
- [Bug]: Negative CUDA graph memory estimation (-35 GiB) with MTP speculative decoding leads to severe KV cache over-allocation and OOM
- [Bugfix] Harden allowed_token_ids metadata for spec-decode
- [Security] Fix remote DoS from grammar-rejected spec tokens padded with -1
- Docs
- Python not yet supported