UNA-SimpleSmaug-34B-v1beta — benchmark results
fblgit's UNA fine-tune of Smaug-34B on the simple-math dataset, applying UNA to attention layers to boost math and reasoning. Provider: Other. Released 2024-02-05. Access: Open.
Unified ELO 1481 ± 17, rank #871 of 1776 rated models, from 14 benchmark results.
Strongest benchmark results
| Benchmark | Score | Metric | Percentile |
|---|---|---|---|
| Open Chinese LLM - WinoGrande | 72.14 | Accuracy (%) | 99.1 |
| Open Chinese LLM - ARC Challenge | 66.04 | Accuracy (%) | 97.3 |
| Open Chinese LLM - C-Eval Semantic | 90.6 | Accuracy (%) | 95.7 |
| Open Chinese LLM - HellaSwag | 71.08 | Accuracy (%) | 95.4 |
| Open Chinese LLM Leaderboard | 69.36 | Average Score (%) | 95 |
| Open LLM Leaderboard - MMLU-Pro | 39.33 | Score | 84.3 |
| Open Chinese LLM - CMMLU | 69.94 | Accuracy (%) | 83.7 |
| Open Chinese LLM - TruthfulQA MC | 59.38 | Accuracy (%) | 81.2 |
| Open Chinese LLM - GSM8K | 56.33 | Accuracy (%) | 77.9 |
| Open LLM Leaderboard - GPQA | 8.95 | Score | 73.2 |
| Open LLM Leaderboard - MuSR | 11.96 | Score | 64.5 |
| Open LLM Leaderboard - BBH | 32.78 | Score | 63 |
Interactive version: theaggregate.ai/model?slug=una-simplesmaug-34b-v1beta · How the rankings work · Data refreshed daily, snapshot 2026-07-22.