Google Introduces Gemma 4 Open-Source AI Model, Enables Building Autonomous Agents

Google, on Thursday, introduced Gemma 4 artificial intelligence (AI) model. The first in the Gemma 4 family comes with several improvements over its predecessors. While Gemma 3 focused on text and visual reasoning capabilities, the Mountain View-based tech giant says the latest iteration brings agentic capabilities and advanced reasoning to the open-source model. Available in four different sizes, the latest large language model (LLM) will be available across Google's developer platforms and can be downloaded via third-party repositories to run locally.

Google Releases Gemma 4

In a blog post, the tech giant announced and detailed the Gemma 4 AI model. The model is available in four different sizes and configurations, including Effective 2B (E2B), Effective 4B (E4B), 26B Mixture of Experts (MoE) and 31B Dense. The context window has also been increased to 256K tokens, up from 128K tokens in Gemma 3. Additionally, it has been trained natively on more than 140 languages.

One big change from the previous generation is that Gemma 4 is now available under the permissible Apache 2.0 license, which allows usage for both academic and commercial purposes. The LLM can be directly used via Google AI Studio and Vertex AI, or can be downloaded from the company's Hugging Face, Kaggle, and Ollama listings.

Three standout features in Gemma 4 are support for advanced reasoning, agentic workflows, and code generation. With advanced reasoning, it is now capable of multi-step planning and deep logic and is said to show improvements in mathematics and instruction following. The model is also capable of functional calling and structured JSON output, letting users power their AI agents with the model.

Additionally, Google claims that the LLM supports high-quality offline code, although it is unclear where it stands compared to proprietary tools, such as Claude Code and Codex. However, the clear advantage here is the free usage and on-device privacy and security.

Other notable feature includes native processing of videos and images with support for variable resolutions. Google claims the model supports visual tasks like OCR and chart understanding. Apart from this, the E2B and E4B models also support native audio input for speech recognition and understanding.