multimaster-7B-v2: benchmark results
An ibivibiv release with a published Mixtral configuration specifying 6 local experts, 2 selected per token and 32 decoder layers. Expert labels and nominal model sizes do not establish total or active learned parameter counts. Provider: ibivibiv. Access: Open.
Aggregate Rating 1457 ± 38, rank #3455 of 10916 rated models, from 6 benchmark results.
Strongest benchmark results
| Benchmark | Score | Metric | Percentile |
|---|---|---|---|
| Open LLM Leaderboard v1 - GSM8K | 71.87 | Accuracy (%) (5-shot) | 96.8 |
| Open LLM Leaderboard v1 - WinoGrande | 84.29 | Accuracy (%) (5-shot) | 92.8 |
| Open LLM Leaderboard v1 - HellaSwag | 87.59 | Normalized accuracy (%) (10-shot) | 87 |
| Open LLM Leaderboard v1 - ARC Challenge | 70.48 | Normalized accuracy (%) (25-shot) | 86.1 |
| Open LLM Leaderboard v1 - MMLU | 65.09 | Accuracy (%) (5-shot) | 81.6 |
| Open LLM Leaderboard v1 - TruthfulQA MC2 | 60.63 | MC2 (%) (0-shot) | 76.3 |
Interactive version: theaggregate.ai/model?slug=multimaster-7b-v2 · How It Works · Data refreshed daily, snapshot 2026-11-08.