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gemma-4-26b-a4b-it

Gemma 4 26B A4B IT is a specialized Mixture-of-Experts (MoE) model designed to bridge the gap between lightweight efficiency and high-parameter reasoning. For developers, the standout feature is its architecture: while the model holds 25.2B total parameters, it only activates approximately 3.8B per token. This allows you to deploy a model with the intelligence profile of a 30B+ parameter dense model while maintaining the low latency and reduced compute costs of a much smaller footprint. It is instruction-tuned for high-precision following, making it ideal for complex RAG pipelines, agentic workflows, and real-time conversational interfaces. Whether you are optimizing for throughput in a production environment or seeking deep reasoning capabilities without the massive VRAM overhead, this model provides a highly efficient scaling path for sophisticated text-based applications.

googletext generation
01 / MODEL CARD

Model card

Gemma 4 26B A4B IT is a specialized Mixture-of-Experts (MoE) model designed to bridge the gap between lightweight efficiency and high-parameter reasoning. For developers, the standout feature is its architecture: while the model holds 25.2B total parameters, it only activates approximately 3.8B per token. This allows you to deploy a model with the intelligence profile of a 30B+ parameter dense model while maintaining the low latency and reduced compute costs of a much smaller footprint. It is instruction-tuned for high-precision following, making it ideal for complex RAG pipelines, agentic workflows, and real-time conversational interfaces. Whether you are optimizing for throughput in a production environment or seeking deep reasoning capabilities without the massive VRAM overhead, this model provides a highly efficient scaling path for sophisticated text-based applications.

Model typetext generation
Providergoogle
LicenseAPI
02 / FILES & VERSIONS

Model files and versions

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Source repositoryhttps://openrouter.ai/google/gemma-4-26b-a4b-it
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03 / DOWNLOAD

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04 / WORKFLOW

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    Read the model card and source information.

  2. 02
    Step 2

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  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

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05 / DISCUSSIONS

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