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arXiv — cs.AIMedHopQA benchmark tests LLM reasoning in biomedical Q&A◆arXiv — cs.CLRouters learn geometry of sparse mixture-of-experts◆arXiv — cs.AIStudy audits how LLMs generate political discourse during crises◆arXiv — cs.AIClassifier Context Rot: Monitor Performance Degrades with Context◆arXiv — cs.AIExecutable Agentic Memory for GUI Agent◆arXiv — cs.CLLongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced◆arXiv — cs.AISparse-to-dense rewards improve language model post-training◆arXiv — cs.AIAI-native mobility dataset advances 6G handover and beam management◆arXiv — cs.AIMedHopQA benchmark tests LLM reasoning in biomedical Q&A◆arXiv — cs.CLRouters learn geometry of sparse mixture-of-experts◆arXiv — cs.AIStudy audits how LLMs generate political discourse during crises◆arXiv — cs.AIClassifier Context Rot: Monitor Performance Degrades with Context◆arXiv — cs.AIExecutable Agentic Memory for GUI Agent◆arXiv — cs.CLLongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced◆arXiv — cs.AISparse-to-dense rewards improve language model post-training◆arXiv — cs.AIAI-native mobility dataset advances 6G handover and beam management◆
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§ local-llm · cluster

vLLM v0.19.0

Apr 3 · · primary fetch1 sourcecluster 4a2e3247updated Apr 3 ·

vLLM v0.19.0 Highlights This release features 448 commits from 197 contributors (54 new)! Gemma 4 support: Full Google Gemma 4 architecture support including MoE, multimodal, reasoning, and tool-use capabilities (#38826, #38847). Requires `transformers>=5.5.0`. We recommend using pre-built docker image `vllm/vllm-openai:gemma4` for out of box usage. Zero-bubble async scheduling + speculative decoding: Async scheduling now supports speculative decoding with zero-bubble overlap, significantly improving throughput (#32951). Model Runner V2 maturation: MRV2 gains piecewise CUDA graphs for pipeline parallelism (#35162), spec decode rejection sampler with greedy/logprobs support (#37238, #37237), multi-modal embeddings for spec decode (#36097), streaming inputs (#37028), and EPLB support (#37488).

ViT Full CUDA Graphs: Vision encoders (ViT) now support full CUDA graph capture for reduced overhead (#35963). General CPU KV cache offloading: A simple yet general CPU KV cache offloading mechanism for V1, with pluggable cache policy and block-level preemption handling (#37160, #37874, #34805, #36642, #37853). DBO (Dual-Batch Overlap) generalization: The microbatch optimization (DBO) now…

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  1. github.comvllm v0.19.0primary