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Move fast and make things: New HART AI generates images 5 times quicker than DALL-E, Imagen 3
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New AI text-to-image generator HART delivers unprecedented speed, creating images in just 1.8 seconds—over 5 times faster than leading diffusion models like DALL-E and Imagen 3. Developed by MIT, Nvidia, and Tsinghua University, HART uses an innovative autoregressive approach that generates images step-by-step rather than through the diffusion process used by most popular generators. This breakthrough demonstrates how different AI training methodologies can dramatically impact performance, potentially setting a new standard for real-time image generation applications.

The big picture: HART (Hybrid Autoregressive Transformer) represents a significant leap forward in AI image generation speed while maintaining comparable image quality to slower competitors.

  • The model can generate images with 3.1 to 5.9 times lower latency than state-of-the-art diffusion models, completing generations in about 1.8 seconds—roughly the time it takes to say “Mississippi.”
  • When tested against OpenAI‘s GPT-4o and Google‘s Imagen 3 using identical prompts, HART generated images 58 times faster than GPT-4o (which took 1 minute 45 seconds) and 5.5 times faster than Imagen 3 (which took about 10 seconds).

How it works: Unlike most popular text-to-image generators that use diffusion models, HART employs an autoregressive (AR) approach similar to OpenAI’s recently released GPT-4o image generator.

  • AR models offer more precise control by generating images sequentially, but traditionally face challenges with training costs and quality at higher resolutions.
  • Researchers overcame these limitations by developing a hybrid tokenizer that processes different parts of the image more efficiently, resulting in both increased speed and higher throughput.

Quality comparison: While HART’s primary advantage is speed, the quality of its outputs remains competitive with leading image generators.

  • In side-by-side comparisons, Google’s Imagen 3 delivered the best balance of speed and quality, though it still took approximately 10 times longer than HART to generate comparable images.
  • According to the article’s author, who has tested most text-to-image models on the market, HART is definitively the quickest available option.

Why this matters: As AI image generation becomes more integrated into creative workflows and applications, the dramatic reduction in generation time could enable new real-time use cases and significantly improve user experience.

Open access: The model is available for free public use and its inference code has been open-sourced through a public GitHub repository, making it accessible to developers, researchers, and AI enthusiasts for further experimentation.

I've tried lots of AI image generators, and Nvidia and MIT's is the one to beat for speed

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