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
- [CI] Improve (NCCL and torch) symmetric memory allreduce test coverage
- [CI Failure]: Import error in test_utils.py
- [RFC]: Batch-Aware Expert Pruning for MoE Decode (XShare)
- [Bug]: MXFP4A16 compressed-tensors quantization produces degenerate output (PPL 22,953 vs 8.74 BF16)
- [Bug]: Subset of Lora unit tests fail on NVIDIA VLLM Stack
- CUDA illegal memory access in MoE layer with MiniMax-M2.5 NVFP4 on Blackwell (SM120)
- [Doc]: Speculative decoding --speculative-config option lacks clear documentation of accepted keys and values
- [ROCm][Quantization] Enable experts_int8 on ROCm
- # [Bugfix]Fix indexError in moe wna16 quantization with enable-expert-parallel
- [Bug]: TTFT latency issue with Qwen3.5-35B-A3B model using vllm
- Docs
- Python not yet supported