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Gemma 4 26B A4B
Gemma 4 26B A4B API combines strong reasoning, natural language processing, and optimized inference efficiency.
Gemma 4 26B A4B delivers a compelling combination of language intelligence, reasoning capability, scalability, and operational efficiency.
Gemma 4 26B A4B is the Mixture-of-Experts (MoE) entry in Google DeepMind's Gemma 4 open model family, released on April 3, 2026. The name is precise: 26 billion total parameters, with 4 billion active on any given token.
The model is built on the same Gemini 3 research architecture that powers Google's proprietary frontier models. It ships under the Apache 2.0 license, meaning it's free to use commercially, modify, and redistribute.
Results below are from instruction-tuned models across standard public evaluations. Gemma 4 26B A4B is compared against its closest open-weight competitors and its immediate family sibling.
Send full legal contracts, research papers, annual reports, or code repositories in a single prompt. The 262K context window means you don't need chunking logic — the model can cross-reference sections and maintain coherence across the whole document.
With native function calling and strong τ²-bench scores, this model is built for agent loops where it needs to plan actions, call tools, process results, and iterate — without losing track of what it was originally asked to do.
Turn on thinking mode for STEM tasks, financial modeling, logic puzzles, and data analysis. The model works through the problem step-by-step in an internal reasoning channel before surfacing a clean answer.
Trained across 140+ languages, this model handles translation, multilingual summarization, and cross-language Q&A without switching between specialized models. One integration, many markets.
Pass entire codebases in-context for refactoring, test generation, documentation, or bug hunting. The long context window is the key differentiator here — smaller models force you to isolate files, which breaks cross-file reasoning.
Send product images for classification, architectural diagrams for explanation, or short video clips for scene analysis. The model handles variable image resolutions without forcing you to pre-resize assets.
The Gemma 4 family gives you real options. Here's how to think about which one fits your workload.
Gemma 4 26B A4B is the Mixture-of-Experts (MoE) entry in Google DeepMind's Gemma 4 open model family, released on April 3, 2026. The name is precise: 26 billion total parameters, with 4 billion active on any given token.
The model is built on the same Gemini 3 research architecture that powers Google's proprietary frontier models. It ships under the Apache 2.0 license, meaning it's free to use commercially, modify, and redistribute.
Results below are from instruction-tuned models across standard public evaluations. Gemma 4 26B A4B is compared against its closest open-weight competitors and its immediate family sibling.
Send full legal contracts, research papers, annual reports, or code repositories in a single prompt. The 262K context window means you don't need chunking logic — the model can cross-reference sections and maintain coherence across the whole document.
With native function calling and strong τ²-bench scores, this model is built for agent loops where it needs to plan actions, call tools, process results, and iterate — without losing track of what it was originally asked to do.
Turn on thinking mode for STEM tasks, financial modeling, logic puzzles, and data analysis. The model works through the problem step-by-step in an internal reasoning channel before surfacing a clean answer.
Trained across 140+ languages, this model handles translation, multilingual summarization, and cross-language Q&A without switching between specialized models. One integration, many markets.
Pass entire codebases in-context for refactoring, test generation, documentation, or bug hunting. The long context window is the key differentiator here — smaller models force you to isolate files, which breaks cross-file reasoning.
Send product images for classification, architectural diagrams for explanation, or short video clips for scene analysis. The model handles variable image resolutions without forcing you to pre-resize assets.
The Gemma 4 family gives you real options. Here's how to think about which one fits your workload.
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