Google Gemma 4

Gemma 4: Byte for Byte, the Most Capable Open Models

Google DeepMind has officially introduced Gemma 4, the most intelligent family of open models to date. Designed to deliver an unprecedented level of intelligence-per-parameter, Gemma 4 is purpose-built for advanced reasoning and complex agentic workflows. This release builds upon the massive momentum of the Gemmaverse, which has seen over 400 million downloads and more than 100,000 variants created by the developer community. By leveraging the same world-class research and technology as Gemini 3, Gemma 4 provides developers with a powerful, accessible, and flexible toolset for the next generation of AI innovation.

What's Gemma 4?

Gemma 4 is a family of lightweight, state-of-the-art open models optimized for high-performance reasoning and efficiency across diverse hardware environments. It bridges the gap between proprietary frontier models and open-source accessibility. Unlike traditional models that rely solely on massive parameter counts, Gemma 4 focuses on maximizing intelligence-per-parameter, allowing it to outperform models significantly larger than itself.

The Gemma 4 family is released under a commercially permissive Apache 2.0 license, ensuring that developers, researchers, and enterprises have complete digital sovereignty and control over their data and infrastructure. Whether running on a mobile device, a developer workstation, or in the cloud, Gemma 4 provides a trusted and transparent foundation for building sophisticated AI applications.

Key Features of Gemma 4

Versatile Model Sizes

Gemma 4 is available in four distinct sizes tailored for specific performance and hardware needs:

• 31B Dense: Maximizes raw quality and provides a powerful foundation for fine-tuning, ranking as the #3 open model globally.
• 26B Mixture of Experts (MoE): Focuses on low latency by activating only 3.8 billion parameters during inference, ranking as the #6 open model globally.
• Effective 4B (E4B) & Effective 2B (E2B): Engineered for mobile-first utility, preserving RAM and battery life while delivering multimodal capabilities.

Advanced Reasoning and Logic

Gemma 4 demonstrates significant improvements in multi-step planning, deep logic, and instruction-following. It excels in math benchmarks and complex problem-solving tasks that require sophisticated cognitive processing.

Native Multimodal Support

All models in the Gemma 4 family can natively process video and images. They support variable resolutions and excel at tasks like Optical Character Recognition (OCR) and chart understanding. The edge-optimized E2B and E4B models also feature native audio input for speech recognition.

Agentic Workflows

Gemma 4 supports native function-calling, structured JSON output, and system instructions. These features enable developers to build autonomous agents capable of interacting with APIs and executing reliable workflows.

Expanded Context Window

To handle long-form content, the edge models offer a 128K context window, while the larger 26B and 31B models provide up to 256K. This allows for the processing of entire repositories or extensive documents in a single prompt.

Global Language Support

Gemma 4 has been natively trained on over 140 languages, making it an ideal choice for building inclusive applications for a global audience.

Use Cases for Gemma 4

"The release of Gemma 4 under an Apache 2.0 license is a huge milestone. We are incredibly excited to support the Gemma 4 family." — Clément Delangue, co-founder and CEO, Hugging Face

1. Mobile and IoT Development

With the E2B and E4B models, developers can create mobile-first AI experiences that run completely offline with near-zero latency. These models are optimized for Android devices, Raspberry Pi, and NVIDIA Jetson Orin Nano.

2. Local AI Coding Assistants

Gemma 4 supports high-quality offline code generation. Developers can turn their workstations into local-first AI coding environments using the 26B and 31B models, ensuring privacy and speed without needing a constant internet connection.

3. Scientific Research

Researchers can fine-tune Gemma 4 for specialized tasks. Previous generations have been used for cancer therapy research (Cell2Sentence-Scale) and creating language-specific models like BgGPT.

4. Enterprise-Grade Agents

Organizations can deploy Gemma 4 to build autonomous agents that handle customer service, data analysis, and tool integration, all while maintaining high standards of security and reliability on-premises or in a Sovereign Cloud.

FAQ

Q: What license is Gemma 4 released under? A: Gemma 4 is released under the Apache 2.0 license, which is commercially permissive and allows for complete developer flexibility.

Q: Which hardware platforms support Gemma 4? A: Gemma 4 is optimized for a wide range of hardware, including NVIDIA GPUs (from Jetson to Blackwell), AMD GPUs via ROCm™, and Google’s TPU infrastructure (Trillium and Ironwood).

Q: How does the 26B MoE model differ from the 31B Dense model? A: The 26B MoE model is designed for speed, activating only 3.8B parameters during inference to provide fast tokens-per-second. The 31B Dense model is built for maximum quality and is the preferred choice for deep fine-tuning.

Q: Can Gemma 4 process audio and video? A: Yes, all Gemma 4 models are multimodal and can process video and images. The E2B and E4B models also include native audio input support for speech-to-text and understanding.

Q: Where can I download the Gemma 4 weights? A: You can download the model weights from Hugging Face, Kaggle, or Ollama.