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Google DeepMind Brings Gemma 4 Open Models to Amazon Bedrock for Enterprise AI

Gemma 4

Google DeepMind has expanded its open-weight model portfolio with the launch of the Gemma 4 family on Amazon Bedrock. This release, announced this week, introduces three instruction-tuned variants designed to maximize intelligence-per-parameter for enterprise applications. The models are available under the Apache 2.0 license, providing developers with flexible deployment options for multimodal tasks and long-context analysis.

The Gemma 4 lineup includes the Gemma 4 31B, the Gemma 4 26B-A4B, and the Gemma 4 E2B. These models utilize a hybrid attention design that enables a context window of up to 256K tokens. This capacity is particularly relevant for Retrieval-Augmented Generation (RAG) and the processing of extensive document sets. Every variant in the family supports native function calling and multimodal inputs, allowing the models to process both text and images simultaneously.

Architectural Efficiency and Mixture-of-Experts

A key technical highlight is the Gemma 4 26B-A4B, which employs a Mixture-of-Experts (MoE) architecture. This specific model contains 25.2 billion total parameters but only activates 3.8 billion parameters during inference. This design aims to provide the performance of a larger model while maintaining the speed and lower compute costs associated with smaller systems. By integrating these models into Amazon Bedrock, AWS provides a managed environment where businesses can scale these open-weight assets without managing underlying infrastructure.

The availability of Gemma 4 on AWS reflects a growing trend of cloud providers hosting high-performance open models alongside proprietary ones. For decision-makers, this offers a path to avoid vendor lock-in while leveraging Google's research through Amazon's cloud ecosystem. The inclusion of native function calling further simplifies the integration of these models into existing enterprise workflows and external APIs.

As of 2026-06-16, developers can access these models to build applications that require high reasoning capabilities within a constrained parameter count. The Gemma 4 family is a strategic move to bridge the gap between lightweight mobile-ready models and massive frontier systems, focusing on efficiency for production-grade AI deployments.

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Introducing Gemma 4 models on Amazon Bedrock

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