<h1>Llama 3.2 Vision Review</h1>
<p>The Llama 3.2 Vision models are designed to excel in various visual recognition tasks, including image reasoning, captioning, and answering image-related questions. These models are available in two parameter sizes: 11 billion (11B) and 90 billion (90B).</p>
<h2>Performance and Evaluation</h2>
<p>The 11B model, while optimized for visual tasks, has shown varying success and is generally not as strong as the Gemini-1.5 Pro model or GPT-4. Its performance has been evaluated across several challenging visual tasks, demonstrating potential but still requiring improvement in some areas.</p>
<p>On the other hand, the 90B model offers significantly better performance but at a greater computational cost. It requires 64GB of VRAM to run, whereas the 11B model only needs 8GB of VRAM. The enhanced capabilities of the 90B model make it more suitable for users with the necessary resources to support it.</p>
<h2>Usage Instructions</h2>
<p>To utilize the Llama 3.2 Vision models, users need to download Ollama 0.4. Once installed, the models can be run via specific commands detailed by Ollama. Example usage includes handwriting recognition, OCR, analyzing charts and tables, and performing image-based Q&amp;A. The documentation provides code snippets for Python, JavaScript, and cURL to help users get started quickly.</p>
<h2>Language Support</h2>
<p>For text tasks, the Llama 3.2 Vision models support multiple languages. However, for combined image and text tasks, currently, only English is supported.</p>
<h2>Conclusion</h2>
<p>Ollama’s support for the Llama 3.2 Vision models presents an exciting opportunity for advancements in visual recognition and image-related queries. While the 11B model provides a manageable entry point, the 90B model offers superior performance for those with sufficient VRAM capacity. Users are encouraged to explore these models further by following the provided installation and evaluation guides, experimenting with their potential, and integrating them into their specific applications.</p>


Collections

The Llama 3.2 Vision models are designed for visual recognition tasks such as image reasoning, captioning, and answering image-related questions, available in two sizes: 11B and 90B parameters. The 11B model offers a lower entry point with 8GB VRAM requirement, while the 90B model, needing 64GB VRAM, provides superior performance. Users can utilize these models via the Ollama 0.4 framework, with support for handwriting recognition, OCR, chart analysis, and image-based Q&A, albeit with some limitations in language support for combined image and text tasks.

Introducing Llama 3.2 Vision: A Comprehensive Look