Trinity-Large-Preview model card (Hugging Face) Jan 27, 2026
- MMLU 87.2
- MMLU-Pro 75.2
- GPQA-Diamond 63.3
- AIME 2025 24
Trinity Large Preview.
Open weights Flagship
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MMLU | 87.2% | #38 of 131 | Lab model card | |
| Vectara Hallucination Leaderboard (2025 dataset) | 6.90% | #31 of 104 | Official leaderboard | |
| LMArena (Elo) | 1,379 | #155 of 335 | Official leaderboard | |
| SimpleQA | 23.9% | #33 of 60 | Lab model card | |
| MMLU-Pro | 75.3% | #109 of 167 | Lab model card | |
| Longform Creative Writing (EQ-Bench) | 35.0 | #107 of 119 | Official leaderboard |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GPQA Diamond | 63.3% | #213 of 302 | Lab model card | |
| AIME 2025 | 24.4% | #139 of 143 | Lab model card |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| PinchBench 2.0 | 53% | #47 of 57 | Official leaderboard | |
| PinchBench | 40.7% | #45 of 48 | Official leaderboard |
The Self-Reported Index fits one score to the 5 capability results Arcee AI reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 119.5 to 128.2. How we compute it.
The benchmarks the lab chose to headline, with the scores it gave.
Every result in the longer documents the lab published with it. 1 of them isn't in the launch post.