Llama 4 Maverick 17B-128E is the largest and most capable Llama 4 model that offers coding, reasoning, and image capabilities. It features Mixture-of-Experts (MoE) architecture with 17 billion active parameters out of 400 billion total parameters and 128 experts. Llama 4 Maverick 17B-128E uses alternating dense and MoE layers, where each token activates a shared expert plus one of the 128 routed experts. The model is pretrained on 200 languages and optimized for high-quality chat interactions through a refined post-training pipeline.
Llama 4 Maverick 17B-128E is multimodal and is suited for advanced image captioning, analysis, precise image understanding, visual questions and answers, creative text generation, general-purpose AI assistants, and sophisticated chatbots requiring top-tier intelligence and image understanding.
Managed API (MaaS) specifications
Try in Agent Studio View model card in Model Garden
| Model ID | llama-4-maverick-17b-128e-instruct-maas |
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| Launch stage | GA | |
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| Knowledge cutoff date | August 2024 | |
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| Pricing | See Pricing. | |
Deploy as a self-deployed model
To self-deploy the model, navigate to the Llama 4 Maverick 17B-128E model card in the Model Garden console and click Deploy model. For more information about deploying and using partner models, see Deploy a partner model and make prediction requests.
Considerations
- You can include a maximum of three images per request.
- The MaaS endpoint doesn't use Llama Guard, unlike previous versions. To use Llama Guard, deploy Llama Guard from Model Garden and then send the prompts and responses to that endpoint. However, compared to Llama 4, Llama Guard has a more limited context (128,000) and can only process requests with a single image at the beginning of the prompt.
- Batch predictions aren't supported.