Twitter/X

Gemma 4-31B reasoning adapter

2026-04-07 · 03:51 UTC ·@outsource_ ·1 min read

Brief

Gemma 4-31B reasoning adapter: a tiny QLoRA fine-tune by @kaiostephens (announced by @outsource_ on 2026-04-07) trained solely on ~1,900 curated Opus reasoning examples, completed in ~1 hour on a single GH200 GPU and released under Apache 2.0. The post claims improved math, code, coherence and personality with no model-size or speed penalty, aimed at local agents and heavy daily workflows.

Source evidence

title: @outsource_: 🤯 GEMMA 4 + OPUS 4.6 REASONING DROPPED

@kaiostephens goal: produce a Gemma 4-31B reasoning adapter ...
author: @outsource_
contenttype: tweet
publication: Twitter/X
published: 2026-04-07T03:51:52+00:00
sourceurl: https://x.com/outsource_/status/2041363302807146680

word_count: 127

🤯 GEMMA 4 + OPUS 4.6 REASONING DROPPED

@kaiostephens goal: produce a Gemma 4-31B reasoning adapter trained only on Opus reasoning 🧠

What the model is:
🧬 Tiny QLoRA adapter on Gemma 4 31B-it
📊 Fine-tuned on ~1,900 curated Opus Examples
⚡ Trained in ~1 hour on a single GH200 GPU
📖 Fully open Apache 2.0

What it does:
✨ Boosts overall quality, coherence, and personality
🧮 Stronger math, code, and Opus problem solving
💬 More refined, thoughtful responses
🏠 Built for local agents, workflows, and heavy daily

Vs base Gemma 4 31B:
📐 Same efficient base model, no extra size or speed
📈 Noticeable step up in real-world depth and quality
💪 Base was already strong this levels It up!

Grab the adapter here 👇🏻
huggingface.co/kai-os/gemma4…