RankingDeepSearchQA
DeepSearchQA
- Bucket
- Agentic
- Unit
- index
- Direction
- Higher is better
- Version
- —
- Display harness
- Muse Spark1.3 evaluation methodology
- Board
- https://research.meta.ai/static/muse-spark-1-3-multimodal-evaluation-methodology
Compare published benchmark results with category weights →
Models
| Model | Score | Harness | Evidence | Source-recorded date |
|---|---|---|---|---|
| GPT-5.6 SolOpenAI | 93.1 percent F1Reported settings & source900questions; common search backend/browser harness; answer-set F1; reasoning max Muse Spark1.3 evaluation methodology · PDF page4 performance table · reviewed 2026-09-06 | Muse Spark1.3 evaluation methodology | lab self-report | 2026-09-06 |
| Claude Opus 5Anthropic | 90.4 percent F1Reported settings & source900questions; common search backend/browser harness; answer-set F1; reasoning max Muse Spark1.3 evaluation methodology · PDF page4 performance table · reviewed 2026-09-06 | Muse Spark1.3 evaluation methodology | lab self-report | 2026-09-06 |
| Muse Spark 1.3Meta | 90.3 percent F1Reported settings & source900questions; common search backend/browser harness; answer-set F1; reasoning max Muse Spark1.3 evaluation methodology · PDF page4 performance table · reviewed 2026-09-06 | Muse Spark1.3 evaluation methodology | lab self-report | 2026-09-06 |
| Muse Spark 1.2Meta | 85.9 percent F1Reported settings & source900questions; common search backend/browser harness; answer-set F1; reasoning xhigh Muse Spark1.3 evaluation methodology · PDF page4 performance table · reviewed 2026-09-06 | Muse Spark1.3 evaluation methodology | lab self-report | 2026-09-06 |
| Muse Spark 1.3Meta | 89.4 percent F1Reported settings & source900questions; common search backend/browser harness; answer-set F1; reasoning xhigh Muse Spark1.3 evaluation methodology · PDF page4 performance table · reviewed 2026-09-06 | Muse Spark1.3 evaluation methodology | lab self-report | 2026-09-06 |