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HiDream-I1: The Open-Source Model That Elevates the Quality of Image Generation
With 17 billion parameters, HiDream-I1 delivers stunning images in various styles, accurately interpreting text prompts and ensuring flexible use with the MIT license
Isabella V8 April 2025

 

HiDream-I1 is an open-source image generation model with 17 billion parameters, capable of producing high-quality images in various styles. It excels at faithfully following text prompts and outperforms other open-source models in GenEval and DPG benchmarks. Distributed under the MIT license, it allows commercial use of the generated images.

Key Points:

  • Superior Image Quality: HiDream-I1 generates outstanding images in various styles, including photorealistic, cartoon, and artistic, achieving high scores in HPS v2.1.
  • Excellent Prompt Interpretation: The model excels in GenEval and DPG benchmarks, outperforming other open-source models in understanding text prompts.
  • MIT Open-Source License: HiDream-I1 is released under the MIT license, promoting innovation and enabling commercial use of the generated images.
  • Available Versions: Both the full version and distilled models are available, adaptable to different computational needs.

In the field of image-generating AI, HiDream-I1 stands out as an advanced open-source model with 17 billion parameters. The model can create superior images in a variety of styles, including photorealistic, cartoon, and artistic. Its performance is demonstrated by high scores in HPS v2.1, a benchmark that measures how closely generated images match human preferences.

A notable aspect of HiDream-I1 is its ability to accurately interpret text prompts. In the GenEval and DPG benchmarks, the model outperformed other open-source models, demonstrating an advanced understanding of the instructions provided.

Released under the MIT License, HiDream-I1 fosters scientific advancement and creative innovation. This license allows the software to be used, modified, and distributed for both personal and commercial purposes, provided that the original copyright notices are retained.

To meet different computational needs, HiDream-I1 is available in multiple versions: the full version and distilled models, which offer a balance between performance and hardware requirements. The model implementation is optimized with the use of Flash Attention, a technique that improves the efficiency of attention computation in transformers.

The adoption of HiDream-I1 is facilitated by the availability of inference scripts that simplify the image generation process. This feature, combined with the open-source nature of the project, makes the model accessible to both researchers and developers interested in exploring the potential of AI image generation. 

HiDream-I1 represents a significant step forward in the field of image generative models, offering a combination of high quality, flexibility and accessibility that makes it a valuable tool for a wide range of applications.