@witcheer: Gemma 4 dropped a 12B. I put it on RTX 5090 against its 31B sibling. when you cut a model from 31B to 12B, what do you …
Summary
A comparison of Gemma 4 12B and 31B models shows that the smaller model retains reasoning capabilities nearly intact but suffers significant knowledge loss, making it ideal for reasoning tasks while the larger model is better for broad knowledge Q&A.
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Cached at: 06/04/26, 04:00 AM
Gemma 4 dropped a 12B. I put it on RTX 5090 against its 31B sibling.
when you cut a model from 31B to 12B, what do you actually lose?
~ reasoning barely moves GSM8K (math) 97.5 > 96.4 (−1.1) ARC-C (sci reasoning) 97.6 > 94.0 (−3.6)
~ knowledge falls off a cliff MMLU (world knowledge) 87.8 > 78.9 (−8.9) HellaSwag (commonsense) 92.0 > 81.6 (−10.4)
parameters store facts, not thinking. the 19B you delete is mostly where the model kept its trivia and world-priors, cut it and recall collapses, while the reasoning machinery stays nearly whole.
a 12B reasons almost like its big brother. It just knows less.
122 tok/s vs 53 (2.3x faster generation), ~10GB instead of ~24, meaning that you get 20GB+ free on a 32GB card for long context or a second model.
so it depends of your workload:
reasoning / math / agentic loops = the 12B is nearly free
broad-knowledge Q&A with no retrieval = that's the one job worth paying for the 31B.Similar Articles
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