openllm-leaderboardconditionalweight 1adapter 14 of 17Leaderboard Rank.
The Open LLM Leaderboard adapter converts leaderboard standing into a percentile component. It counts only for models on the leaderboard, turning an external, independently maintained ranking into a directly comparable 0–100 component.
What it measures.
Percentile
Leaderboard position expressed as a 0–100 percentile.
Independent evaluation
Ranking produced by the leaderboard’s own benchmark suite.
Component keys.
openllm-leaderboard.*Component family covering leaderboard standing.
When it counts.
Conditional — applies only to models listed on the Open LLM Leaderboard.
When signals are missing.
Unlisted models compute without this component.
How it contributes.
{
"component": "openllm-leaderboard.*",
"scale": "0-100",
"mode": "conditional",
"weight": 1,
"contribution": "component x 1 / total weight"
}The adapter’s components are averaged into the composite as a weighted mean: every contributing adapter’s component is multiplied by its weight, summed, and divided by the total weight of contributing adapters. The result is published as trustScores.total with a config version and timestamp so anyone can recompute it.
Questions about Leaderboard Rank.
What does the Open LLM Leaderboard adapter contribute?
It converts a model’s Open LLM Leaderboard position into a percentile component (openllm-leaderboard.*) at weight 1.
Does it apply to agents or only models?
Only models on the leaderboard. It is a conditional adapter for model subjects and does not count for other subject types.