Yi-34B-200K-DARE-merge-v7: benchmark results
Provider: brucethemoose. Access: Open.
Aggregate Rating 1524 ± 30, rank #2017 of 10916 rated models, from 14 benchmark results.
Strongest benchmark results
| Benchmark | Score | Metric | Percentile |
|---|---|---|---|
| Open LLM Leaderboard v1 - MMLU | 77.3 | Accuracy (%) (5-shot) | 98.5 |
| Open Chinese LLM - WinoGrande | 70.4 | Accuracy (%) | 93.8 |
| Open Chinese LLM - ARC Challenge | 61.6 | Accuracy (%) | 91 |
| Open Chinese LLM - C-Eval Semantic | 88.91 | Accuracy (%) | 89.8 |
| Open Chinese LLM - HellaSwag | 68.61 | Accuracy (%) | 88.6 |
| Open LLM Leaderboard v1 - WinoGrande | 83.11 | Accuracy (%) (5-shot) | 87.1 |
| Open Chinese LLM Leaderboard | 67.09 | Official Nonzero-Task Mean (%) | 86.1 |
| Open Chinese LLM - CMMLU | 70.21 | Accuracy (%) | 85.8 |
| Open LLM Leaderboard v1 - GSM8K | 65.35 | Accuracy (%) (5-shot) | 79.9 |
| Open LLM Leaderboard v1 - ARC Challenge | 68.09 | Normalized accuracy (%) (25-shot) | 79.3 |
| Open LLM Leaderboard v1 - HellaSwag | 85.99 | Normalized accuracy (%) (10-shot) | 77.9 |
| Open Chinese LLM - GSM8K | 54.51 | Accuracy (%) | 74.7 |
Interactive version: theaggregate.ai/model?slug=yi-34b-200k-dare-merge-v7 · How It Works · Data refreshed daily, snapshot 2026-11-08.