Llama 3.2 90B Vision Instruct

Llama 3.2 90B Vision Instruct is a state-of-the-art multimodal large language model developed by Meta that combines strong language understanding with advanced vision capabilities. The model is designed to handle both text-only and vision-language tasks, making it versatile for a wide range of applications. With 90 billion parameters, it offers a balance between capability and computational efficiency, positioning itself as a strong alternative to closed-source vision models. The instruction-tuned variant has been optimized through supervised fine-tuning and reinforcement learning from human feedback (RLHF) to follow user instructions accurately and provide coherent, contextually relevant responses. The model supports an 8K token context window, enabling it to process longer documents and multi-image sequences. Llama 3.2 represents a significant advancement in open-source multimodal AI, providing researchers and practitioners with a powerful tool for building vision-language applications without proprietary API dependencies. The model excels at image captioning, visual question answering, document understanding, and complex reasoning tasks that combine visual and textual information.