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Meta (Llama)text+image->text

Meta: Llama 3.2 11B Vision Instruct

Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis. Its ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research. Click here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md). Usage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

Context Window

131K

Input Price

$0.0500/M tokens

Output Price

$0.0500/M tokens

Modality

text+image->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.0500/M tokens
Output$0.0500/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.000550

Context Window Size
Maximum tokens the model can process in a single request
Context Window131K tokens
13% of 1M max

~98K

Words Equivalent

~66

Pages of Text

~1311

Code Functions

Best Use Cases
What this model excels at
WritingContent-creationMathReasoningAnalysisVisionImage-analysisMultimodalData-analysisAnalyticsResearchAcademic

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