# Gemma Dev

Trigger this skill when building applications with Gemma or for general knowledge...

- Repository: https://github.com/google-gemma/gemma-skills (1038 stars)
- Category: AI and agents
- License: Apache-2.0
- Last updated: 2026-10-28
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add google-gemma/gemma-skills --skill gemma-dev -g -a claude-code -y`
Codex: `npx skills add google-gemma/gemma-skills --skill gemma-dev -g -a codex -y`
Cursor: `npx skills add google-gemma/gemma-skills --skill gemma-dev -g -a cursor -y`
Gemini CLI: `npx skills add google-gemma/gemma-skills --skill gemma-dev -g -a gemini-cli -y`

## Description

Trigger this skill when building applications with Gemma or for general knowledge inquiries related to Gemma models (e.g. prompt structure, capabilities). Covers model selection, development workflows, and deployment best practices.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Gemma Development Skill

## 1. Core Principle: Prioritize App Tooling

**DO NOT** generate raw PyTorch, TensorFlow, or `transformers` code unless the
user explicitly asks for "Training," "Fine-tuning," or "Research." Always
default to high-level frameworks, SDKs, and tooling optimized for application
development.

## 2. Model Selection Guide

**CRITICAL:** Do not blindly default to `gemma-3-1b-it`. You must analyze the
user's specific domain, technical constraints, and required input modalities to
recommend the exact right fit. When recommending standard models, strictly
default to the **Gemma 4** generation. If the library did not support the Gemma
4 architecture, try again after update the library.

### Core Gemma Models

All Gemma 4 models feature **Thinking Mode**, enabling advanced reasoning to
process complex logic, math, and multi-step problems before generating a
response.

-   Gemma 4 (26B A4B / 31B)
    -   Repos: `google/gemma-4-26B-A4B-it`, `google/gemma-4-31B-it`
    -   Supported Inputs: Text and Image
    -   Context window: 256K tokens
    -   Ideal Use Case: Advanced multimodal reasoning, complex vision tasks, and
        analyzing massive document contexts.
    -   Note: The 26B A4B utilizes a highly efficient Mixture-of-Experts for
        fast, heavy-weight reasoning, alongside the dense 31B variant.
-   Gemma 4 (12B)
    -   Repos: `google/gemma-4-12B-it`
    -   Supported Inputs: Text, Image, **Audio**
    -   Context window: 256K tokens
    -   Ideal Use Case: Multimodal reasoning (including audio), inference in
        laptops, and consumer devices.
-   Gemma 4 (E2B / E4B)
    -   Repos: `google/gemma-4-E2B-it`, `google/gemma-4-E4B-it`
    -   Supported Inputs: Text, Image, **Audio**
    -   Context window: 128K tokens
    -   Ideal Use Case: Mobile NPU acceleration; on-device workflows explicitly
        requiring native audio processing alongside robust reasoning.

### Legacy & Lightweight Models (Gemma 3)

The rest: https://github.com/google-gemma/gemma-skills/blob/HEAD/skills/gemma-dev/SKILL.md