docs

What is AI model verification? Evidence and limitations

AI model verification compares a third-party API's observed behavior with a selected official reference. It provides evidence about model identity, not cryptographic proof of the model running behind a gateway.

← Back to docs

Model verification compares endpoint behavior against official model fingerprints, while benchmark scores serve as a reference for capability comparison rather than a promise about any one provider.

This matters when you buy access through gateways, proxy layers, or region-specific resellers and need evidence that the endpoint behaves like the advertised model family.

The public product is designed to show verdicts, latency, drift, and stability signals without revealing protected prompts, probes, expected answers, thresholds, or internal rule ordering.