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Released April 2, 2026 — Fully Open Source

Google Gemma 4

The most capable open AI model family. Four variants from phone to server. Apache 2.0 licensed.

Google DeepMind's biggest open-source release yet — built from Gemini 3 research, ranking #3 globally on Arena AI, and outperforming models 10x its size. Here's everything you need to know and every way to access it.

4Model Variants
#3Open Model Rank
Apache 2.0License
256KMax Context

Section 01

Model Variants

Four sizes optimized across the hardware spectrum — from smartphones to servers.

01

Gemma 4 E2B

Phones & IoT — runs offline on low-RAM devices

Total Params

5.1B

Effective

~2.3B

Layers

35

Context

128K

TextImageAudio

Best for: On-device AI, mobile apps, offline agents, Raspberry Pi

02

Gemma 4 E4B

Edge devices — vision + audio on consumer hardware

Total Params

8B

Effective

~4.5B

Layers

42

Context

128K

TextImageAudio

Best for: Edge deployment, real-time processing, embedded systems

03

Gemma 4 26B A4B

Mixture-of-Experts — dense quality, MoE speed

Total Params

25.2B

Effective

3.8B active

Layers

30

Context

256K

TextImage

Best for: Fast inference, long-context tasks, consumer GPUs

04

Gemma 4 31B

Flagship — #3 open model globally at 1452 ELO

Total Params

30.7B

Effective

30.7B

Layers

60

Context

256K

TextImage

Best for: Maximum performance, complex reasoning, agentic workflows

Section 02

Gemma 4 vs Gemma 3

Gemma 4 31B vs Gemma 3 27B. The improvements are generational.

1452

Arena ELO

#3

Open Model Globally

#1

US Open-Source Model

Benchmark
Gemma 3 27B
Gemma 4 31B
MMLU Pro
67.6%
85.2%
GPQA Diamond
42.4%
84.3%
AIME 2026
20.8%
89.2%
BigBench Extra Hard
19.3%
74.4%
LiveCodeBench v6
29.1%
80%
MMMU Pro (Vision)
49.7%
76.9%

Section 03

What's New in Gemma 4

Six reasons this isn't just an incremental update.

Apache 2.0 License

Fully open-source for the first time. Unrestricted commercial use, modification, and deployment — no previous license restrictions.

Intelligence-per-Parameter

Massive gains via better training data, distillation techniques, and Gemini 3 research. BigBench Extra Hard jumps from 19.3% to 74.4%.

Native Multimodal

Vision across all variants. Audio on edge models. Interleaved text/image prompts. Video support up to 60s at 1 FPS.

256K Context Window

Hybrid attention with interleaved local sliding-window and global attention layers for stable long-context performance.

Built for Agents

Native function calling, tool use, and multi-step planning. Agentic benchmark (t2-bench) leaps from 6.6% to 86.4%.

Runs Anywhere

From phones and Raspberry Pi to single GPUs and cloud servers. NVIDIA-optimized quantization (NVFP4) for Blackwell hardware.

Section 04

Where to Access Gemma 4

Every official way to try, download, and deploy — all free to start.

Google AI Studio

Try Gemma 4 instantly in your browser. Free tier with full multimodal support — text, image, and audio prompts.

Try Free in Browser

Hugging Face

Download all 8 variants (base + instruction-tuned) with model cards and developer resources.

Download Weights

Ollama

One command to run locally: ollama run gemma4. Supports all sizes including edge variants.

Run Locally

Kaggle

Official mirror with notebook integration. Great for experimentation and quick prototyping.

Open on Kaggle

Vertex AI

Production deployment on Google Cloud. Fine-tuning, managed endpoints, GKE, TPU support.

Deploy on Cloud

Google AI Edge

Run E2B and E4B on Android, iOS, and edge devices. Optimized for mobile via AI Edge Gallery.

Build On-Device

Section 05

Official Resources

Direct links to everything from Google DeepMind.

Official Announcement Blog Post

Blog

Full Model Card (Architecture, Benchmarks, Safety)

Docs

DeepMind Gemma 4 Overview

Docs

Get Started Guide & Documentation

Docs

"What's New in Gemma 4" — Official Launch Video

Video

"How to Build On-Device AI with Gemma 4"

Video

GitHub — Examples & Tools

GitHub

Apache 2.0 License Details

Docs

Want to build with Gemma 4?

Knowing which model to use is step one. Learning how to deploy it, build agents around it, and stay ahead as these models evolve monthly — that's where the real advantage is.

Follow @mattfarmerai for practical AI guides, quick reviews, and plain-English takes on what each release actually changes.

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