Pareto
You're paying frontier prices for requests that don't need them.
Most teams run one model for everything, so an easy lookup costs the same as a hard reasoning task, and switching models per job rarely happens in practice. We built Pareto to fix that: a blended model we recompose per request, so cheaper execution handles the easy work and frontier reasoning only kicks in when it's earned.
See the full model cardPareto vs. Opus 4.8
The bill, drawn to scale
In practice
Evidence, not a promise.
We don't want Pareto to feel like a black box. We'll give you ongoing proof it's earning its keep, and full control over how much of your traffic actually runs through it.
Find your AI stack-
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Performance reports. We'll send you regular reports comparing Pareto against your base model, on your own traffic, not a synthetic leaderboard.
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Your model's own opinion. We ask your base model to grade Pareto's responses, so the read isn't just ours.
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Traffic and cost you control. Dial the split between Pareto and your base model up or down, any time. Completely pay-as-you-go.
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No thumb on the scale. When another model wins for a task, we say so and route you there. Pareto only keeps the traffic it earns.
The method
Why you can trust the numbers.
Every claim we make about Pareto is tied to a named comparison model, a representative task, a stated method, and evidence you can check.
Read the evaluation FAQTested on your work
We evaluate using tasks like the ones you actually run, not synthetic leaderboards.
Same conditions, every time
We run your base model and Pareto through the same prompts, same harness, same day, so the comparison means something.
Blind where it counts
When we bring in human judgment, our reviewers don't know which model wrote it.
No claims before the evidence
We don't publish a performance, price, or reliability claim until we can back it up.
Test Pareto on your work.
Bring a real workload. We'll get you set up with prepaid usage and schedule guided onboarding.