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# Model Routing Is Simple. Until It Isn’t.

**[Hugging Face](https://daily.dev/sources/huggingface)** · 5 min read · 0 upvotes · 0 comments

## Summary

Building model routing into agentic systems is harder than it looks. IBM Research shares three key lessons from real-world experience: (1) actual cost depends on caching behavior, not just token pricing — Claude Sonnet 4.6 ended up cheaper than GPT-4.1 on the same workload due to cache hit rates; (2) task complexity is invisible at routing time and must be balanced against cost, latency, compliance, and reliability simultaneously; (3) latency is driven by serving infrastructure, not just model size. Their solution reframes routing as a multi-objective optimization problem rather than a classification problem, achieving a 21% cost reduction and 9% latency reduction with only a 4% accuracy drop compared to running a single large model, while keeping the router itself lightweight at ~6ms and 2kB per task.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://huggingface.co/blog/ibm-research/model-routing-is-simple-until-it-isnt>

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- [Token Spend Out of Control? The Case for Smarter Routing](https://daily.dev/posts/token-spend-out-of-control-the-case-for-smarter-routing-jxkbskjha) · ByteByteGo · 3 upvotes · 0 comments

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