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Caption Images

These models generate text descriptions and captions from images. They use large multimodal transformers trained on image-text pairs to understand visual concepts.

Key capabilities:

  • Image captioning: Produce relevant captions summarizing image contents and context. Useful for indexing images and accessibility. Automate alt text for images.
  • Visual question answering: Generate natural language answers to questions about images. Ask questions about your images.
  • Text prompt generation: Create prompts matching image style and content. Use images to guide text-to-image generation.

Our pick: Moondream 2B

Moondream is an efficient, versatile vision language model. It offers a great balance of intelligence to cost, and it can give a detailed caption in just seconds.

A more powerful model: LLaVa 13B

For most people, we recommend the LLaVa 13B model. LLaVa can generate full paragraphs describing an image in depth. It also excels at answering questions about images insightfully.

Budget pick: BLIP

If you need to generate a large volume of image captions or answers and don't require maximum detail or intelligence, BLIP is a great choice. It performs nearly as well as the more advanced but slower BLIP-2, which makes it significantly cheaper per request

However, BLIP is less capable than Moondream or LLaVa at generating long-form text or exhibiting deeper visual understanding. Stick with our top pick if you need those advanced capabilities.

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