Llama 3.2 Vision 11b vs Llama 4 Scout
Compare Llama 3.2 Vision 11b and Llama 4 Scout side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Llama 3.2 Vision 11b vs Llama 4 Scout Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Llama 3.2 Vision 11b | Llama 4 Scout |
|---|---|---|
| Organization | Meta | Meta |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2024 | Apr 2025 |
| Context Window | 128K | 10.0M |
| Parameters | 11B | 109B |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | |
| Output $/1M | $0.300 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| Object Detection | ||
| Model Features | ||
| Multimodal Vision | ||
| LLMs with Vision Capabilities | ||
Llama 3.2 Vision 11b vs Llama 4 Scout: Overview
Llama 3.2 Vision 11B, released by Meta on September 25, 2024, is the first mid-sized model in the Llama family with vision capabilities, supporting both text and image inputs with text-only outputs. It contains around 11 billion parameters (~10.6B) and features a 128,000-token context window, making it suitable for multimodal reasoning over long documents and image-text tasks. The model was trained on ~6 billion image–text pairs and has a knowledge cutoff of December 2023.
The model is available in a base and an instruction-tuned (“Vision-Instruct”) version, optimized for tasks like captioning, visual question answering, and image reasoning. It leverages Group-Query Attention (GQA) for improved inference efficiency and scalability. While text tasks officially support multiple languages (English, German, French, Italian, Portuguese, Hindi, Spanish, Thai), multimodal (image+text) tasks are supported primarily in English. Llama 3.2 Vision 11B is accessible through Hugging Face, Amazon Bedrock, Azure AI Foundry, NVIDIA NIM, and OCI, making it a widely deployable open-weight multimodal foundation model.
Llama 4 Scout, released on April 5, 2025, is one of Meta AI’s first Llama 4 multimodal models, alongside Maverick. It accepts text + image inputs and produces text outputs, with a knowledge cutoff of August 2024. Scout is notable for its extremely large context window of 10 million tokens, making it well-suited for analyzing very long documents, extended conversations, or large codebases.
Architecturally, Scout uses a Mixture-of-Experts (MoE) system with 16 experts, activating ~17B parameters per inference from a pool of ~109B total parameters, balancing capacity with efficiency. It officially supports 12 languages (including English, Arabic, French, Hindi, and Spanish), while offering multimodal reasoning for images (captioning, Q&A, recognition). Meta highlights that Scout can run on a single Nvidia H100 GPU, making it more accessible than larger-scale Llama 4 models. However, its output token limit is far smaller than its 10M input window, image input support is still constrained, and license restrictions apply for large-scale commercial deployments.