# SWEAtlas CodeBase QnA — AI model rankings

Questions about how an unfamiliar codebase actually works — where something is handled, what a change would touch — answered by reading the repository rather than editing it. Tests understanding rather than patch-writing. Higher is better.

2 tracked models have a published SWEAtlas CodeBase QnA 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 | 59.4% | Lab | Sep 2 2026 |
| 1 | Mistral Large 4 | Mistral | 59.4% | Lab | Oct 6 2026 |


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Canonical page: https://aireleasetracker.com/benchmark/sweatlas-codebase-qna
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.