Running multimodal models like Llama 3.2 Vision on Ollama?

All answers to this question.

Does the Ollama vision model handle complex tables and charts well for data extraction?

   Answered 2025-01-02 by Arthur Knight

• Arthur, it's decent for simple tables, but for high-fidelity chart data, you might want to try the Qwen2-VL model in Ollama. It was specifically trained for document understanding and often outperforms Llama on technical diagrams. The great thing about Ollama is you can pull both and switch between them with a single API parameter change to see which one handles your specific marketing assets better.

     Commented 2025-01-10 by Victor Malone

I used it for alt-text generation for my blog. The Ollama output was perfect and saved me a week of work.

   Answered 2025-01-20 by Pamela Boyd

• That’s a perfect use case, Pamela. Using Ollama for batch processing images is free, whereas cloud APIs would cost a fortune for thousands of images.

     Commented 2025-01-25 by Bryan Foster

Yes, Ollama has excellent support for multimodal models like Llama 3.2 Vision and Moondream. In the API request, you just include an images array with your base64 strings. For a 16GB Mac, Llama 3.2 11B Vision is the sweet spot. It’s incredibly fast at describing product images or extracting text from messy screenshots. Because of the unified memory in Apple Silicon, Ollama can swap the vision encoder in and out of the GPU very efficiently, which usually takes much longer on traditional Windows setups with split RAM/VRAM.

   Answered 2025-12-15 by Monica Foster