AI Research
Beyond Accuracy and Cost: Latency-Aware LLM Query Routing for Dynamic Workloads
Modern language query routers improve inference efficiency by assigning each query to a model that balances response quality and monetary cost. However, current query routers are largely latency-agnostic and do not consider the generation latency experienced by queries at model i...
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ArXiv CS.AI
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ArXiv CS.AI
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This research introduces a novel latency-aware approach to routing queries to large language models, moving beyond just accuracy and cost. By estimating and optimizing for response time, it can significantly improve the overall efficiency and perceived performance of LLM applications.
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