# DeepSearchQA — AI model rankings

Questions that cannot be answered from one page: the AI has to search the web, follow the trail across several sources, and put the pieces together into an answer. Higher is better.

1 tracked model have a published DeepSearchQA score. Higher is better. Scores come from published lab reports and benchmark sources; recorded sources appear beside the scores.

## Ranking

| Rank | Model | Developer | Score | Source | Released |
| --- | --- | --- | --- | --- | --- |
| 1 | Muse Spark 1.3 | Meta | 89.4% | Lab | Sep 2 2026 |


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Canonical page: https://aireleasetracker.com/benchmark/deepsearchqa
Site index: https://aireleasetracker.com/llms.txt
Source: AI Release Tracker (https://aireleasetracker.com). Most benchmark scores come from lab launch material; gathered results identify the leaderboard that published them.