SWE-bench Verified hard subset (Meta)
Agents fix the hardest SWE-bench Verified issues. Meta uses about 42 tasks and a 50% indicative threshold for AI R&D risk.
Meta's own hard subset. It may differ from Anthropic's SWE-bench Verified hard subset.
- Made by
- Meta
- Released
- April 2026
- Kind
- Fixing real repositories
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Code
- Tasks
- All public
- Strongest model tested
-
Muse Spark #53 on the capability index
- Last in a system card
- June 2026
- Last model added
- June 2026
Muse Spark leads with 42.9%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1
Muse Spark 42.9%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 42.9% | Jun 2026 | Lab model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Jun 12, 2026 | | 42.9 | SWE-Bench Verified (hard subset) (2.3.1.1 text) | AI R&D risk |
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