IBM Research: LLM routing is a systems optimization problem
LangChain · x · 2026-07-20
IBM Research argues that LLM routing should be treated as a systems-optimization problem rather than a pure classification task.
The key example: Claude Sonnet 4.6 ended up costing about half as much as GPT-4.1 per task because caching effects dominated the economics, even though its sticker price was higher.
The takeaway is that real-world routing decisions need to account for infrastructure-level effects such as cache reuse, not just headline pricing or model labels.
Related event: IBM Research: LLM Routing is a System Optimization Problem(2 posts)→
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