smol_bruin-7B: benchmark results
Azazelle's SLERP merge, whose published recipe uses mistralai/Mistral-7B-v0.1 as its base and rwitz/go-bruins-v2, rishiraj/smol-7b as merge inputs. Its published Mistral configuration specifies 32 decoder layers. Provider: Azazelle. Access: Open.
Aggregate Rating 1441 ± 34, rank #4180 of 10916 rated models, from 6 benchmark results.
Strongest benchmark results
| Benchmark | Score | Metric | Percentile |
|---|---|---|---|
| Open LLM Leaderboard v1 - GSM8K | 70.43 | Accuracy (%) (5-shot) | 93 |
| Open LLM Leaderboard v1 - HellaSwag | 86.48 | Normalized accuracy (%) (10-shot) | 81.3 |
| Open LLM Leaderboard v1 - MMLU | 65.05 | Accuracy (%) (5-shot) | 80.9 |
| Open LLM Leaderboard v1 - ARC Challenge | 67.58 | Normalized accuracy (%) (25-shot) | 77.4 |
| Open LLM Leaderboard v1 - WinoGrande | 81.14 | Accuracy (%) (5-shot) | 77.4 |
| Open LLM Leaderboard v1 - TruthfulQA MC2 | 55.65 | MC2 (%) (0-shot) | 65.7 |
Interactive version: theaggregate.ai/model?slug=smol-bruin-7b · How It Works · Data refreshed daily, snapshot 2026-11-08.