---
title: "Introducing Gemma 4 models on Amazon Bedrock"
slug: "google-deepminds-gemma-4-landet-als-managed-service-in-amazon-bedrock"
date: 2026-06-15
category: tech-pub
tags: [google, reasoning, amazon]
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/google-deepminds-gemma-4-landet-als-managed-service-in-amazon-bedrock
---

# Introducing Gemma 4 models on Amazon Bedrock

**Published**: 2026-06-15 | **Category**: tech-pub | **Sources**: 1

---

## TL;DR

- AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.

---

## Summary

- AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.
- All three variants support text and image input, built-in reasoning mode, and native function calling. The larger 31B and 26B-A4B models offer context windows up to 256K tokens.
- The lineup mixes dense and MoE designs. Gemma 4 26B-A4B has 25.2B total parameters but activates 3.8B per token, while E2B targets low-cost, low-latency multimodal jobs.
- Access runs through AWS's bedrock-mantle endpoint with OpenAI-compatible Chat Completions and Responses APIs. The announcement is clearly framed for managed production GenAI use.

---

## Why it matters

AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.

---

## Key Points

- AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.
- All three variants support text and image input, built-in reasoning mode, and native function calling. The larger 31B and 26B-A4B models offer context windows up to 256K tokens.
- The lineup mixes dense and MoE designs. Gemma 4 26B-A4B has 25.2B total parameters but activates 3.8B per token, while E2B targets low-cost, low-latency multimodal jobs.
- Access runs through AWS's bedrock-mantle endpoint with OpenAI-compatible Chat Completions and Responses APIs. The announcement is clearly framed for managed production GenAI use.

---

## Nauti's Take

Open weights get truly useful when they hit boring enterprise reality: IAM, data controls, service tiers, API compatibility. Gemma 4 on Bedrock is not hobbyist candy. It is another lever for pushing agent stacks out of notebooks and into controlled production.

---


## FAQ

**Q:** What is Introducing Gemma 4 models on Amazon Bedrock about?

**A:** - AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.

**Q:** Why does it matter?

**A:** AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.

**Q:** What are the key takeaways?

**A:** AWS is adding Google DeepMind's Gemma 4 family to Amazon Bedrock: three instruction-tuned Apache 2.0 open-weight models named Gemma 4 31B, 26B-A4B, and E2B.. All three variants support text and image input, built-in reasoning mode, and native function calling. The larger 31B and 26B-A4B models offer context windows up to 256K tokens.. The lineup mixes dense and MoE designs. Gemma 4 26B-A4B has 25.2B total parameters but activates 3.8B per token, while E2B targets low-cost, low-latency multimodal jobs.

---

## Related Topics

- [google](https://news.ainauten.com/en/tag/google)
- [reasoning](https://news.ainauten.com/en/tag/reasoning)
- [amazon](https://news.ainauten.com/en/tag/amazon)

---

## Sources

- [Introducing Gemma 4 models on Amazon Bedrock](https://aws.amazon.com/blogs/machine-learning/introducing-gemma-4-models-on-amazon-bedrock/) - AWS Machine Learning Blog
- [Introducing container caching in Amazon SageMaker AI for faster model scaling](https://aws.amazon.com/blogs/machine-learning/introducing-container-caching-in-amazon-sagemaker-ai-for-faster-model-scaling/) - AWS Machine Learning Blog

---

## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

---

*Last Updated: 2026-06-17*