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
- [Model][MRV2] Support pipeline parallelism for DiffusionGemma
- [Bug]: logs from a parser loaded with --tool-parser-plugin bypass vLLM's logging config
- [Usage]: RuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}
- [Feature] Add opt-in dynamic NVFP4 MoE GEMM2 quantization
- [RFC]: LoRA adapter support for DFlash speculative decoding draft models
- [Bug]: Gemma 4 31B MTP - Slower T/S at high context
- [Bug]: gpt-oss-120b MXFP4 + --enable-expert-parallel crashes at startup: modular MoE finalize allocates padded (3072) output for an unpadded (2880) expert result
- [Feature][DSpark]: Evaluate STS for online DSpark confidence alignment
- [Feature][DSpark]: Improve Adaptive DSpark Online Profiling
- [ROCm][Perf] Split MiniMax-M3 prefill index-score K loop
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