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deepmind.google·6d ago
AI Engineering
Hugging Face Blog·20d ago·5 min read
Model Routing Is Simple. Until It Isn’t.
TL;DR
Model routing in AI systems is more complex than simply selecting the cheapest model based on pricing. A study revealed that GPT-4.1, despite lower token costs, was more expensive than Claude Sonnet due to caching effects.
✦ Why It Matters
Evaluate caching strategies in your model routing systems to ensure accurate cost assessments and optimize performance.
Key Takeaways
- Consider caching effects when evaluating model costs.
- Balance multiple factors like cost, latency, and compliance in routing.
- Optimize routing as a system problem, not just model selection.
- Test different configurations to find the best operating point.
How It Works
The new routing algorithm optimizes across cost, quality, and latency by evaluating the entire system's performance rather than just selecting models based on task difficulty. It incorporates caching behavior and infrastructure state to enhance decision-making.