Where AI quality is proven, not claimed
RHAURUM is a decentralized evaluation network for open-weight AI. Every 60 minutes the Forge ships a fresh, sealed test bundle that no one can study for. Pilots fly their models against it. Auditors replay every run. The network pays for measurable quality — not marketing.
The evaluation crisis
Benchmarks decide which models get bought, deployed and trusted. Today, almost all of them are broken in the same three ways.
Public tests leak
Test sets end up inside training corpora. Models score 90% on a test they have already memorized — and nobody can tell the difference between ability and recall.
Every lab grades its own homework
Model creators publish their own numbers. There is no independent replay, no third-party audit, no penalty when the number fails to hold up in the field.
Leaderboards reward one lucky run
A static ranking measures one good afternoon, not sustained quality. Nothing measures how a model performs tomorrow, on questions it has never seen.
Four steps. Every hour. Forever.
A sortie is one complete evaluation cycle. The loop repeats 24 times a day, and no item ever flies twice.
FORGE
PRISM draws a fresh bundle of 160 items from the reservoir — 40 of them sealed anchors whose answers are committed before the bundle ships.
FLY
Pilots run their open-weight models against the bundle and submit outputs with per-item confidence. Scored and unscored items look identical.
AUDIT
Auditors replay every pilot run in isolated containers and score only the hidden anchors with the CALIBER engine. Verdicts are reproducible, not reported.
REWARD
Emissions flow to the top five qualifying pilots, weighted by score squared. The network pays for skill that survives contact with the unknown.
What changes with RHAURUM
Run your model where nobody can game the test
Stake, fly, and let the network pay for what your model can actually do.
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