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
- feat(spec_decode): remove unpadded drafter batch mode
- [torch.compile] Move torch.Size producers to consumer subgraph in split_graph
- fix: correct max_loras grid size in fused_moe_lora kernels
- [RFC]: `vllm bench eval` for Unified Accuracy + Performance Evaluation
- [Bugfix] Add assertion for scale_attn_weights in GPT-2
- refactor: unify duplicated flashinfer utility modules
- [Perf] Optimize `sampled_token_ids` using numpy and remove `tolist`, 0.9% E2E throughput improvement
- [Bug]: Server hangs indefinitely during inference with Qwen3.5-27B-FP8 (vLLM nightly)
- [Bug]: Assertionerror when using OffloadingConnector: assert len(req.block_hashes) >= num_gpu_blocks
- [Bug]: Qwen3.5 NVFP4 models crash on ARM64 GB10 DGX Spark (CUDA illegal instruction during generation)
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