The first answer is free or cheap. The ongoing watch — keeping you on the cheapest model that still clears your bar as the market moves — is the subscription, and where the value sits.
Add-on: a shareable detailed report of any run — per-example breakdown, every metric, recommendation — $9. Included with Monitoring.
Standard judges on accuracy alone — free, and enough for many tasks. Advanced lets you set a bar across worst-class accuracy, latency, format validity, consistency, cost and hallucination rate, so "good enough" means what it actually means for you. It's $1 per run.
A one-off verdict goes stale the week a new model ships. The value isn't the first answer — it's staying on the cheapest model that still clears your bars over time, without you re-checking. That's the subscription.
For objectively-gradable tasks — classification, extraction — we grade programmatically against your labelled examples. No expensive LLM-judge in the loop, so re-testing costs us almost nothing and we can do it continuously.
The whole comparison-and-inference stack runs inside your environment on open models, with the eval grounded in your own data — and, at scale, a small distilled model fine-tuned to your task that you run and own. Pricing's bespoke; start a conversation.
Run your first bake-off, see the verdict, then decide if staying current is worth $29.
Try the demo →