Slerp-CM-mist-dpo: benchmark results
abacusai's Slerp-CM-mist-dpo, an experimental SLERP merge of cookinai's CatMacaroni-Slerp and mncai's mistral-7b-dpo-v5, intended for research use only. Provider: Abacus.AI. Released 2024-01-03. Access: Open.
Aggregate Rating 1446 ± 23, rank #1000 of 1635 rated models, from 19 benchmark results.
Strongest benchmark results
| Benchmark | Score | Metric | Percentile |
|---|---|---|---|
| Open LLM Leaderboard v1 - GSM8K | 72.78 | Accuracy (%) (5-shot) | 98.1 |
| Open LLM Leaderboard v1 - HellaSwag | 87.09 | Normalized accuracy (%) (10-shot) | 84.5 |
| Open LLM Leaderboard v1 - ARC Challenge | 69.62 | Normalized accuracy (%) (25-shot) | 83.7 |
| Open Chinese LLM - TruthfulQA MC | 59.82 | Accuracy (%) | 82.8 |
| Open Portuguese LLM - FaQuAD NLI | 78.05 | Macro F1 (%) | 82.5 |
| Open LLM Leaderboard v1 - TruthfulQA MC2 | 62.82 | MC2 (%) (0-shot) | 79.8 |
| Open LLM Leaderboard v1 - WinoGrande | 81.45 | Accuracy (%) (5-shot) | 79.3 |
| Open Portuguese LLM - ASSIN2 RTE | 92.4 | Macro F1 (%) | 78.7 |
| Open LLM Leaderboard v1 - MMLU | 64.81 | Accuracy (%) (5-shot) | 77 |
| Open Portuguese LLM - ENEM | 65.43 | Accuracy (%) | 61.7 |
| Open Portuguese LLM - BLUEX | 53.69 | Accuracy (%) | 56.8 |
| Open Chinese LLM - GSM8K | 47.23 | Accuracy (%) | 56.2 |
Interactive version: theaggregate.ai/model?slug=slerp-cm-mist-dpo · How It Works · Data refreshed daily, snapshot 2026-11-05.