Llama 4 Maverick 17B
Llama 4 Maverick is Meta's multimodal, mixture-of-experts model in the Llama 4 family, packing 17 billion active parameters within a larger MoE architecture that activates only a subset of weights per token. This design delivers strong performance across text and image understanding tasks with better compute efficiency than a dense model of equivalent total parameter count.
Maverick is the more capable and flexible sibling to Llama 4 Scout, offering native image input support alongside text. It suits applications requiring visual question answering, document understanding with embedded images, and complex instruction following where both modalities are involved.
Key Features
Mixture-of-experts architecture for efficient high-capacity inference
Native multimodal input supporting both text and images
Strong visual question answering and image-grounded reasoning
17B active parameters balancing quality and deployment cost
Open weights enabling fine-tuning across modalities
Competitive benchmark performance in the Llama 4 generation
Ideal Use Cases
Visual document analysis with charts, diagrams, or scanned pages
Multimodal customer support combining image and text inputs
Image-captioning and visual content moderation pipelines
Research prototyping requiring open multimodal model access
Instruction-following applications spanning text and image tasks
Example Prompts for Llama 4 Maverick 17B
Technical Specifications
| Provider | Meta |
| Category | Text |
| Modality | Text -> Text |
Frequently Asked Questions
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