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All digests tagged Model Routing
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Sydney Runkle details how to build a model router in the harness to reduce operational costs. By analyzing task traces and selecting models along the Pareto frontier, the router cut median cost per thread by 64%.
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Suraj Gupta details three ways software factories self-improve: using outer-loop agents for skill refinement, implementing persistent memory for traceable facts, and optimizing costs via model routing. Learn how to build self-improving agentic workflows.
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NeMo Switchyard is an open-source model routing library for AI agents that automatically routes each query to the best available model. It solves the 'one model' problem by optimizing selection across local/cloud and open/closed models.
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Model routing argues that there is no single best LLM. By using a purpose-built Mixture of Experts model, developers can dynamically select the optimal AI model per request based on cost, latency, and task type.
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Model routing is evolving from simple task-based selection to complex orchestration, requiring systems that can adapt when tasks change state—from question to feature request to live debugging.
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