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A new open-source architecture called Mixture of Models (MoM) for Large Language Models, which bundles multiple AI models to function like a Mixture of Experts model, is released on GitHub.
MERA introduces a multi-cycle adaptation approach for LLM agents that improves small models by distilling execution-verified demonstrations into a SkillBook and fine-tuning LoRA adapters, with router-based deployment and verifier-backed fallback. Experiments show Qwen2.5-Coder-1.5B improves from 28.7% to 49.7% pass on HumanEval++MBPP while retaining most quality at lower cost.
Clement Delangue highlights vLLM's new semantic router, an open-source system for routing LLM queries to the most appropriate model, aiming to shift value from expensive frontier models to a diverse ecosystem of open-source models.