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Model Details
Model Provider
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Model Tree
Qwen/Qwen3-14B
Input Modalities
Output Modalities
Supported Functionality
| model | score | size |
|---|---|---|
| Mistral Large 3 | 0.825 | 675B |
| gloofy-14b (this) | 0.816 | 14B |
| gloofy-4b (clean labels) | 0.808 | 4B |
| Kimi K2.5 | 0.791 | MoE |
| Gemma 3 27B | 0.731 | 27B |
| Llama 3 70B | 0.725 | 70B |
| GPT-OSS 120B | 0.701 | 120B |
Second of eight — tied with the 675B leader within measurement error (n=150), ahead of every other model, at 48x smaller. The exam v3.1 was ~19% mislabeled; v3.3 corrects it (Opus overrode 142/750 gold fields).
The lever was clean labels, not size: training on Opus labels lifted the 4B from 0.796 to 0.808; 14B adds +0.008. A distilled model matches the frontier when its teacher is clean.
markdown
from peft import PeftModelfrom transformers import AutoModelForCausalLMm = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B")m = PeftModel.from_pretrained(m, "overads/gloofy-14b")