# ARC-AGI score curves link v1 and v2 results across models

> Original title: Plotting ARC-AGI model scores reveals a strong relationship across all three benchmarks.

- Source: ARC Prize
- Published: 2026-10-28T16:05:36.000Z
- Bad Influence: https://badinfluence.news/items/tkoc046hx55m96bq4x7c2q3sv
- Original: https://x.com/arcprize/status/2115475078175395986

## Summary

ARC Prize says ARC-AGI-2 scores follow a power curve, v2 = v1^4.53, that explains about 98% of the variation in scores. Models tied on ARC-AGI-1 can still differ by over 20 percentage points on ARC-AGI-2.

## Post

Plotting ARC-AGI model scores reveals a strong relationship across all three benchmarks.

For example, the power curve v2 = v1^4.53 explains about 98% of the variation in ARC-AGI-2 scores. Models tied on ARC-AGI-1 can still differ by over 20 percentage points on ARC-AGI-2.

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHVutX2sWkAAuPiL.jpg&mode=thumb&exp=1793404800&sig=35c56dd9f0d8df6e)