Free AI Image Alt Text Generator

Effortlessly generate descriptive alt text for your images using our AI-powered tool. Improve accessibility and SEO without a hassle.

Write alt text for this image...

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JPG, PNG, GIF files less than 10MB

JPG, PNG, GIF files less than 10MB

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What Is Image Alt Text?

Image alt text, often referred to simply as "alt text," is a descriptive attribute added to HTML code to provide a textual description of an image on a web page. Alt text serves two primary purposes: accessibility and SEO (Search Engine Optimization).

  • Accessibility. Alt text is vital for making web content accessible to individuals with visual impairments or those who use screen readers. When an image has alt text, the screen reader reads the text aloud, enabling users to understand the image's content and context. Alt text ensures that people who cannot see the image can still comprehend the information it conveys, making websites more inclusive.
  • SEO (Search Engine Optimization). Alt text also plays a role in optimizing web content for search engines. Search engines like Google cannot interpret images like humans can. Alt text provides a textual description that helps search engines understand the image's content. When images have relevant and descriptive alt text, they can be indexed and appear in image search results, improving the website's overall visibility and potentially driving more organic traffic.

In essence, image alt text serves as a bridge between the visual content of images and the digital interpretation required by accessibility tools and search engines. Writing informative and concise alt text is essential to provide equal access to information and enhance a website's accessibility and SEO efforts.

The technology behind Ahrefs’ Image Alt Text Generator

Ahrefs’ Image Alt Text Generator uses a language model that learns patterns, grammar, and vocabulary from large amounts of text data – then uses that knowledge to generate human-like text based on a given prompt or input. The generated text combines both the model's learned information and its understanding of the input.

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