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Behind the comparison

Methodology

Know what a ranking measures before you choose an AI model. Here is how to read the reference results and use them in your creative workflow.

What Oakgen curates

Oakgen Arena presents a dated OpenArt reference snapshot with original guidance for choosing image and video models. These scores are OpenArt's published results. Oakgen has not conducted or independently reproduced this evaluation.

One snapshot, clearly dated.

Index version 1.0 was published on September 15, 2026. We collected the public results on October 30, 2026 UTC.

The collection contains seven video boards and five image boards. Changing a category selects another published board. Sorting a table changes its display order, never the source rank or score.

How OpenArt ranks models

Blind pairs

Judges compare outputs without model identities, using one named criterion at a time.

Relative scores

A Bradley-Terry model estimates criterion scores relative to a fixed anchor.

Published weights

Board scores combine criteria using the snapshot's weights. Some general fits are reused across boards.

Show uncertainty

The source uses judge-cluster bootstrap estimates for 95% confidence intervals.

Read OpenArt's full methodology ↗

A score is a comparison, not a quality grade

Read the score together with its interval and the task being evaluated. A small numerical lead deserves caution when estimates overlap. An ordinal rank alone does not establish a meaningful difference. Compare models within the same board. Different criteria and weights make cross-board score comparisons misleading.

The Anchor label identifies the model used to fix the scale. Its missing interval is labeled explicitly. It does not mean that the model has no uncertainty.

Keep the gaps visible

This snapshot does not report composite distinct-judge counts or prices. We leave those values unknown. Vote appearances are not unique voters and must not be added across boards. Reused criterion fits are identified where the source supplies that information.

Raw votes and the complete generation history are not part of this collection. We cannot audit prompt selection, retries or individual judging decisions from aggregate scores.

Build a shortlist. Then test your brief.

Choose a board that matches your task, then compare a few models with the same prompt and reference assets. Record the model version, settings, cost and failures. Inspect the details your project needs, such as text accuracy or subject consistency. Check current availability and licensing separately before production.

Compare your own image prompt →