Deploying Multimodal Models on RunPod

Multimodal AI models, which integrate diverse data types such as text, images, audio, and video, enable tasks like image-text retrieval and video question answering but pose challenges in terms of high computational requirements and scalability. RunPod offers a cloud platform optimized for AI workloads, facilitating the deployment of these models by providing detailed instructions and necessary infrastructure, including various GPU instances to accommodate different model sizes. For instance, smaller models like CLIP/BLIP can run on an A40 GPU, while larger models might require an A100, H200, or multiple GPUs. The platform supports containerization and API design for efficient model serving, emphasizing the need for regular updates and performance monitoring to maintain cost-effectiveness and efficiency over time.