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Google DeepMind Advanced

Gemma 3 12B IT

Gemma 3 12B IT is Google's multimodal instruction model with text and image input, 128K context and support for more than 140 languages.

Text GenerationText Freemium
In plain English

What is this model and why does it matter?

Gemma 3 12B IT is Google's multimodal 12B instruction model with text and image input, text output and a 128K context window.

Multimodal assistantsImage understandingLong-document analysisLocal AIMultilingual applications
Model overview

Gemma 3 12B IT: features, use cases and important details

Gemma 3 12B IT is a multimodal instruction-tuned Google model released as part of the Gemma 3 family in March 2025.

Verified model facts

Google documents text and image input, generated text output, a 128K context window for the 12B size and multilingual support across more than 140 languages.

Best fit

It fits multimodal assistants, image understanding, long-document analysis and multilingual self-hosted applications.

Limitations

It can make visual and factual errors, requires significant memory at 12B scale and remains subject to Google’s Gemma terms.

Get started

How to use this model

  1. Accept the Gemma terms.
  2. Download the official 12B instruction checkpoint.
  3. Load it with a supported Gemma runtime.
  4. Provide text and optional image inputs using the documented format.
  5. Evaluate outputs for accuracy and safety.
Copy and try

Example prompts

  • Describe the important information in this chart.
  • Compare this image with the written specification.
  • Summarize this long document in Spanish.
Capabilities

What it can do

  • Text generation
  • Image understanding
  • 128K context
  • Multilingual support
  • Instruction following
Best for

Practical use cases

  • Visual Q&A
  • Document analysis
  • Multilingual assistants
  • Local multimodal applications
Pricing

What does it cost?

Open-weight checkpoint under the Gemma terms; no dedicated per-token provider price applies to this downloadable checkpoint.

Simple summaryWeights are available under the Gemma terms. Serving cost depends on hardware or cloud infrastructure.

What stands out

  • 128K context
  • Image plus text input
  • 140+ languages
  • Official Google open weights

Things to consider

  • 12B deployment still needs capable hardware
  • Custom Gemma terms
  • Text-only output
Limitations

Important restrictions and trade-offs

  • Image reasoning can be wrong
  • Static knowledge
  • Large context does not guarantee reliable recall across an entire prompt
SimplifyAITools verdict

Our editorial take

A strong open-weight Google option for multimodal and multilingual self-hosted applications that need substantially longer context than Gemma 2.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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