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
- [Bug]: Silent generation stall (Avg generation throughput drops to 0.0, no errors, /health and /v1/chat/completions still return 200) on Qwen3.5-397B-A17B / Qwen3.5-397B-A17B-FP8 / Qwen3.5-122B-A10B across v0.18.0, v0.19.0, v0.25.1
- [CI Perf] Trimming the tests for the hybrid models
- [bot] Enable google/gemma-4-E2B-it-qat-mobile-ct inference on Intel XPU
- [Feature]: Native SM120 backend for Quark/OCP MXFP6 (Dense and Qwen3.5 MoE)
- [hw-agnostic] Adding embedding layer and lm_head
- [Refactor] Refactor EPD
- [Bugfix][CPU] Fail fast when MLA head dimensions are not supported by the CPU decode kernel
- [Kernel] Add tuned fused_moe config for NVIDIA GB10 (Nemotron-3-Super shape, E=512 N=2688)
- [Quantization] Add Stage 1 (CPU-only, reference) BitNet ternary quantization backend
- [Bugfix][LoRA] Fix PEFT 0.18+ target_parameters LoRA loading for 3D MoE experts
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