RankingMRCR · v2 512K-1M
MRCR · v2 512K-1M
- Bucket
- Long context
- Unit
- index
- Direction
- Higher is better
- Version
- v2 512K-1M
- 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 |
|---|---|---|---|---|
| Muse Spark 1.3Meta | 98.1 percent sequence matchReported settings & source8needle;100examples/band rebinned byo200k_base; no tools; sequence-matcher ratio; GPT fromOpenAIcard; 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 |
| GPT-5.6 SolOpenAI | 73.8 percent sequence matchReported settings & source8needle;100examples/band rebinned byo200k_base; no tools; sequence-matcher ratio; GPT fromOpenAIcard; 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 | 55.5 percent sequence matchReported settings & source8needle;100examples/band rebinned byo200k_base; no tools; sequence-matcher ratio; GPT fromOpenAIcard; 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 | 93.1 percent sequence matchReported settings & source8needle;100examples/band rebinned byo200k_base; no tools; sequence-matcher ratio; GPT fromOpenAIcard; 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 |