Estimate your LLM cost savings
TTU Router reduces inference costs by routing easy queries to smaller, cheaper models, only escalating to expensive models when the small model is uncertain. Based on verified benchmarks with N=1,000 queries.
How it works
Your application sends requests to the TTU proxy instead of directly to your LLM provider.
A proprietary quality assessment determines whether the query needs the full model or can be handled by a more efficient one.
Simple queries are handled efficiently. Complex queries get the full model. You get quality where it matters, savings where it doesn't.
With TTU: $195/mo
Quality retained: 99.8% (verified, N=1,000)
Methodology
Savings estimates are based on our verified benchmark: 1,000 MMLU queries routed between GPT-4o-mini and GPT-4o. At the optimal threshold, 51% of queries were handled by the small model with 99.8% quality retention. Your actual savings depend on query complexity distribution, which varies by use case. The “routable to small model” slider lets you adjust this assumption.
Routing overhead is 0.16μs per decision (measured over 10,000 decisions), six orders of magnitude below typical API latency. Zero perceptible impact on user experience.
Want to test with your real data?
We can run a free proof-of-concept with your actual API traffic to measure exact savings.