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
- [Quantization] Clarify MXFP4 MoE W13 layout requirement from backends
- [Bug]: Cannot run KimiLinearForCausalLM (Kimi-K3-0.40B) on CPU — MLA vs Mamba prefix-caching conflict
- [bug]: empty JSON schema `{}` causes unbounded number death-loop garbled output
- [Bugfix][Qwen3.5-MTP] Load a dedicated mtp.lm_head draft head
- [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
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- Python not yet supported