# Building a Local, Multimodal AI Terminal Agent with Gemma 4

DevFeed: [Building a Local, Multimodal AI Terminal Agent with Gemma 4](<https://devfeed.tech/articles/building-a-local-multimodal-ai-terminal-agent-with-gemma-4-22852.md>)

Original publisher: [Read original article](<https://medium.com/google-developer-experts/building-a-local-multimodal-ai-terminal-agent-with-gemma-4-4fbaa50eb14b?source=rss----a67bd6fa7d58---4>)

Author: Arjun Prabhulal

Published: 2026-08-12T09:25:11Z

Content type: tutorial

Language: en

Sources: [Google Developer Experts - Medium](<https://devfeed.tech/sources/google-developer-experts-medium.md>)

Topics: [gemma4](<https://devfeed.tech/topics/gemma4.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [multimodal-ai](<https://devfeed.tech/topics/multimodal-ai.md>), [Command-line interface](<https://devfeed.tech/topics/cli.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [Code](<https://devfeed.tech/topics/code.md>), [Google](<https://devfeed.tech/topics/google.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [code](<https://devfeed.tech/tags/code.md>), [function-calling](<https://devfeed.tech/tags/function-calling.md>), [gemma](<https://devfeed.tech/tags/gemma.md>), [gemma-4](<https://devfeed.tech/tags/gemma-4.md>), [google](<https://devfeed.tech/tags/google.md>), [google-cloud-platform](<https://devfeed.tech/tags/google-cloud-platform.md>), [local-ai](<https://devfeed.tech/tags/local-ai.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [ollama](<https://devfeed.tech/tags/ollama.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [terminal](<https://devfeed.tech/tags/terminal.md>)

## AI overview

A tutorial introduces Gemma 4 and builds a local multimodal terminal agent named gemma4-agent. It covers function calling, tool orchestration, text, image, and voice processing, plus Gemma 4's model variants and architecture.

## Source excerpt

Introduction Open-source LLM models have been improving rapidly with tool calling, extended context windows, and native vision and audio capabilities, all while delivering strong benchmark performance. Gemma 4, recently introduced by Google Deepmind brings all of these features together in sizes efficient enough to run locally. In this article, we'll look at the capabilities of Gemma 4 and build a multimodal (Text, Vision, Voice) CLI agent (gemma4-agent) with function-calling capabilities. By the end, you'll have an agent that can chat, write, execute code, analyze images, and process voice instructions to deliver highly grounded responses. What is Gemma 4 Model ? Gemma 4 is Google DeepMind's open model family, released in April 2026 under the Apache 2.0 license. Built from the same research and technology behind Gemini 3, Gemma 4 is designed for high-performance reasoning, coding, multimodal understanding, and local AI execution across different model sizes. Features of Gemma 4 Models Improved Tool calling : Native function calling and tool orchestration, letting agents act autonomously without bloating prompt instructions Thinking mode : Built-in step-by-step thinking mode via the <|think|> token for complex multi-turn logic Context Windows : Up to 256K tokens on the 12B and larger models (128K on the edge-sized E2B/E4B) for processing long document and tool outputs Extended Multimodality : Gemma 4 models can process text,voice and images simultaneously like extracting data from charts, analyzing screenshots , and reviewing UI mockups. Gemma 4 Model Variants & SpecificationsGemma 4 Architecture Gemma 4 comes in five model sizes built around four architectural variants, each making different trade-offs between performance, inference speed, compute, and memory. Gemma4 Unified 12B vs Effective Parameters Effective-parameter models (E2B and E4B) are dense transformer models optimized for edge and on-device deployment. The "E" stands for effective parameters use Per-La