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Gemma 4 26B A4B IT

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Gemma 4 26B A4B IT is Google's open-weight mixture-of-experts model with 26B total parameters and roughly 4B active per forward pass. Built on the Gemini 3 architecture, it supports function-calling, structured JSON output, native vision, and 140+ languages within a context window of 262.1K tokens.

Vision (Image)Tool UseFile Input
index.ts
import { streamText } from 'ai'


const result = streamText({
  model: 'google/gemma-4-26b-a4b-it',
  prompt: 'Why is the sky blue?'
})

What To Consider When Choosing a Provider

  • Configuration: Evaluate whether the MoE architecture's latency and throughput characteristics fit your workload before selecting a provider variant at production scale.
  • Zero Data Retention: AI Gateway supports Zero Data Retention for this model via direct gateway requests (BYOK is not included). To configure this, check the documentation.
  • Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

When to Use Gemma 4 26B A4B IT

Best For

  • Latency-sensitive production workloads: The MoE architecture's lower compute-per-token translates to faster response times
  • Cost-efficient agentic pipelines: Need function-calling and structured output at high request volumes
  • Multilingual applications: Serving users across 140+ languages with a single model
  • Vision-language tasks: Image understanding, visual Q&A, and document analysis within a context window of 262.1K tokens
  • Open-weight workloads: The ability to inspect model weights matters

Consider Alternatives When

  • Highest output quality needed: Latency is not a constraint, and the dense Gemma 4 31B or a Gemini model may be more appropriate
  • Native image or audio generation: Your task requires media output, which Gemma 4 26B A4B IT does not support
  • Simple classification or extraction: A smaller, cheaper model is sufficient for straightforward workloads

Conclusion

Gemma 4 26B A4B IT provides Gemini 3-class capabilities in an open-weight package optimized for throughput. The MoE architecture keeps inference fast and affordable. For teams that need strong multilingual, multimodal reasoning without proprietary lock-in, it is a practical production choice on AI Gateway.

Frequently Asked Questions

  • What does mixture-of-experts mean for Gemma 4 26B A4B IT?

    Gemma 4 26B A4B IT has 26B total parameters split across expert sub-networks. A routing mechanism activates roughly 4B parameters per forward pass, selecting the most relevant experts for each input. This reduces compute per token compared to a dense model of equivalent total size.

  • How does Gemma 4 26B A4B IT compare to the dense Gemma 4 31B?

    Gemma 4 26B A4B IT prioritizes latency and throughput by activating fewer parameters per token. The dense Gemma 4 31B activates all 31B parameters, targeting higher output quality at the cost of more compute. Choose Gemma 4 26B A4B IT when speed matters and the dense variant when quality is the priority.

  • What input modalities does Gemma 4 26B A4B IT support?

    Gemma 4 26B A4B IT accepts text and image inputs. It does not generate images or audio. Use it for text generation, visual understanding, and structured output tasks.

  • What languages does Gemma 4 26B A4B IT support?

    Over 140 languages. The instruction-tuning covers multilingual conversational and task-oriented use cases.

  • How do I use Gemma 4 26B A4B IT on AI Gateway?

    Set the model to google/gemma-4-26b-a4b-it in the AI SDK. AI Gateway handles provider routing, retries, and failover automatically.

  • Does Gemma 4 26B A4B IT support function-calling and structured output?

    Yes. It supports function-calling for agentic workflows, structured JSON output, and system instructions natively, sharing these capabilities with the Gemini 3 architecture it is built on.