google/gemma-4-26B-A4B

Overview

Google DeepMind's Gemma 4 26B A4B is a multimodal Mixture-of-Experts (MoE) model, part of the Gemma 4 family, designed for frontier-level performance. It processes text and image inputs, with a focus on efficient deployment on consumer GPUs and workstations. The model features a hybrid attention mechanism for speed and long-context awareness, and supports a substantial 256K token context window.

Key Capabilities

• Multimodal Input: Handles text and image inputs, with variable aspect ratio and resolution support.
• Efficient Architecture: Utilizes a Mixture-of-Experts (MoE) design with 25.2 billion total parameters and 3.8 billion active parameters, enabling fast inference.
• Reasoning & Coding: Designed as a highly capable reasoner with configurable thinking modes and enhanced coding benchmarks, including native function-calling support.
• Extended Context: Supports a 256K token context window, crucial for complex, long-context tasks.
• Native System Prompt Support: Introduces native support for the system role for structured conversations.

Good For

• Reasoning and Agentic Workflows: Its strong reasoning capabilities and function-calling support make it ideal for autonomous agents.
• Coding Tasks: Excels in code generation, completion, and correction.
• Multimodal Understanding: Suitable for applications requiring both text and image processing, such as object detection, document parsing, and UI understanding.
• Fast Inference: The MoE architecture allows it to run almost as fast as a 4B-parameter model, making it efficient for deployment.