Google has announced the launch of Gemma 4, its most advanced family of open models to date. Designed for advanced reasoning and agentic workflows, the new release sets a benchmark in intelligence-per-parameter, making high-performance AI more accessible across devices and developer environments.
Building on the success of its predecessors, Gemma has already seen over 400 million downloads and fostered a thriving ecosystem of more than 100,000 variants globally. With Gemma 4, Google is doubling down on its commitment to democratizing AI, offering cutting-edge capabilities under a commercially permissive Apache 2.0 open-source license.
A New Benchmark in AI Performance and Efficiency
Built using the same foundational research behind Gemini 3, Gemma 4 introduces a powerful blend of efficiency and performance. The model family is available in four configurations, including Effective 2B and 4B models for edge deployment, alongside 26B Mixture of Experts and 31B Dense variants for high-performance workloads.
Despite their relatively compact sizes, the larger models have demonstrated exceptional performance on global benchmarks. The 31B variant ranks among the top open models worldwide, while the 26B model closely follows, outperforming significantly larger systems. This leap in efficiency allows developers to achieve near frontier-level AI capabilities without requiring extensive computational infrastructure.
Designed for Advanced Reasoning and Agentic Workflows
Gemma 4 moves beyond traditional conversational AI by enabling complex, multi-step reasoning and autonomous task execution. With native support for structured outputs, function calling, and system-level instructions, the models are purpose-built for agentic workflows where AI systems can interact with tools, APIs, and external data sources.
The models also bring strong improvements in mathematics, logic, and instruction-following benchmarks, positioning them as a powerful foundation for building next-generation AI applications across industries.
Here is what makes Gemma 4 our most capable open model family yet:
Advanced reasoning: Capable of multi-step planning and deep logic, Gemma 4 demonstrates significant improvements in math and instruction-following benchmarks that require it.
Agentic workflows: Native support for function-calling, structured JSON output, and native system instructions enables you to build autonomous agents that can interact with different tools and APIs and execute workflows reliably.
Code generation: Gemma 4 supports high-quality offline code, turning your workstation into a local-first AI code assistant.
Vision and audio: All models natively process video and images, supporting variable resolutions, and excelling at visual tasks like OCR and chart understanding. Additionally, the E2B and E4B models feature native audio input for speech recognition and understanding.
Longer context: Process long-form content seamlessly. The edge models feature a 128K context window, while the larger models offer up to 256K, allowing you to pass repositories or long documents in a single prompt.
140+ languages: Natively trained on over 140 languages, Gemma 4 helps developers build inclusive, high-performance applications for a global audience.
Multimodal Intelligence Meets Edge Computing
A key highlight of Gemma 4 is its multimodal capability across all model sizes. The models can process images, video, and text natively, with edge variants additionally supporting audio input for speech recognition and understanding.
The E2B and E4B models are specifically engineered for on-device AI, offering low-latency performance and efficient memory usage. Through collaborations with mobile ecosystem leaders such as Qualcomm Technologies and MediaTek, these models are optimized to run offline on smartphones, IoT devices, and compact systems like Raspberry Pi and NVIDIA Jetson platforms. Integration with Androidโs AI Core further enables developers to build and test agentic applications directly on-device.
Scalable AI Across Hardware Environments
Gemma 4 is designed to scale seamlessly across a wide range of hardware, from mobile devices to high-performance GPUs. The 26B and 31B models can run efficiently on developer workstations and enterprise-grade accelerators, including setups powered by NVIDIA GPUs.
The Mixture of Experts architecture in the 26B model ensures faster inference by activating only a fraction of its parameters, while the 31B Dense model focuses on maximizing output quality, making it ideal for fine-tuning and specialized applications.
Empowering Innovation with Open Access
Reinforcing its open innovation strategy, Google has released Gemma 4 under the Apache 2.0 license, offering developers complete flexibility to build, customize, and deploy AI solutions across environments. This approach not only reduces barriers to entry but also supports digital sovereignty by giving organizations full control over their data and infrastructure.
The impact of previous Gemma models has already been visible across research and enterprise use cases, including collaborations with institutions like INSAIT and Yale University. With Gemma 4, Google aims to further expand these possibilities, enabling breakthroughs in areas ranging from language AI to healthcare research.
Driving the Future of Open AI Ecosystems
With Gemma 4, Google is positioning itself at the forefront of the open AI movement, delivering a powerful alternative to proprietary systems while maintaining compatibility with its broader AI ecosystem. By combining efficiency, scalability, and openness, the company is equipping developers with the tools needed to build intelligent, inclusive, and globally scalable applications.
As the demand for accessible and high-performance AI continues to rise, Gemma 4 stands out as a transformative step toward making advanced AI capabilities available to everyone, from individual developers to large enterprises
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