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
- [fuse_norm_quant] Support mixed input/weight dtype in fused RMSNorm+FP8 quant kernels (fixes Qwen3.5-FP8)
- [DiffusionGemma-26B-A4B-it][XPU] Fix DiffusionGemma for TP>1 and enable XPU
- [Tracking] Enable MiMo-V2.5-Pro-FP4 with DFlash speculative decoding
- [DiffusionGemma-26B-A4B-it FP8][XPU][Quant] Enable native XPU FP8 MoE for per-token dynamic activations
- [DiffusionGemma-26B-A4B-it-NVFP4 ][XPU][Quant] Register NVFP4 emulation linear kernel for XPU
- [DSV4][XPU] sycl optimization for _fused_kv_compress_norm_rope_insert_sparse_attn kernel
- [Misc] Rename VLLM_TRITON_ATTN_USE_TD to VLLM_TRITON_USE_TD
- [Misc] benchmark_moe: support Gemma4 architectures
- [Feature][SP] Support Sequence Parallelism for Multimodal Encoder
- [Frontend] Add `/v1/messages/render` endpoint for the Anthropic Messages API
- Docs
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