Gemma 4, Optimized
for Real Hardware

Run powerful AI on your CPU, mobile device, or edge hardware. 51% faster inference, 50%+ smaller models, fully local and private.

51% Faster Inference

57% Size Reduction

100% Local & Private

Get Started → View on GitHub

🦙 Ollama Hub 🤗 Hugging Face 💬 Discord Community 📊 Kaggle Submission 🔬 Research Article 👤 Developer Blog

Choose Your Model Family

From multimodal powerhouses to ultra-lightweight mobile models, optimized for every use case.

MULTIMODAL

gemma4-turbo

Full-featured AI with vision and audio support

+51%

Faster

IQ4_XS

Quantization

4.3-18 GB

Model Sizes

20.5K+

Downloads

Vision and audio capabilities
51% faster than stock Gemma 4
5 model sizes (e2b, e4b, 12b, 26b, 31b)
Tool calling and function support
Windows-optimized for CPU inference

Ollama Hub Hugging Face

ULTRA-LIGHTWEIGHT

gemma4-nano

Mobile-first AI that actually works on real devices

57%

Smaller

Q3_K_S

Quantization

3.1-14 GB

Model Sizes

2.7K+

Downloads

Text-only, optimized for mobile/edge
Sub-1GB RAM usage (891.7 MB total)
Stays cool on 8GB RAM phones
Full 4.5B params, 128K context
13% faster than turbo on CPU

Ollama Hub Hugging Face

COMING SOON

More Variants

Pushing the boundaries of AI optimization

🚀

In Progress

∞

Possibilities

Experimental quantization methods
Specialized task-optimized variants
Even smaller mobile models
Performance tuning research
Community-driven development

Follow on GitHub

*Note: Hugging Face download counts displayed on their model cards reflect a rolling 30-day window rather than permanent cumulative downloads. Our stats counters automatically baseline and sum permanent, absolute community downloads.

Get Started in Seconds

One command to run powerful local AI on your hardware

Option 1: Ollama (Recommended)

# Install Ollama from https://ollama.com

# For multimodal AI with vision:
ollama run ssfdre38/gemma4-turbo:e4b

# For ultra-lightweight mobile/edge:
ollama run ssfdre38/gemma4-nano:e2b

# That's it! Start chatting with local AI 🚀

Option 2: Direct GGUF Download

# Download from Hugging Face:
wget https://huggingface.co/ssfdre38/gemma4-turbo-gguf/resolve/main/gemma4-e4b-iq4xs-turbo.gguf

# Use with llama.cpp, Ollama, or any GGUF-compatible tool

Model Size Guide

# Turbo (multimodal):
e2b   → 4.3 GB   # Smallest with vision
e4b   → 6.1 GB   # Recommended default
12b   → 6.9 GB   # Balanced multimodal
26b   → 15 GB    # High capability
31b   → 18 GB    # Maximum performance

# Nano (text-only):
e2b   → 3.1 GB   # Mobile-ready
e4b   → 4.7 GB   # Balanced
12b   → 5.7 GB   # Balanced reasoning
26b   → 12 GB    # High quality
31b   → 14 GB    # Best performance

Gemma 4, Optimized for Real Hardware