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HiDream-O1-Image-Pro - A flagship image model from Zhixiang Future

HiDream-O1-Image-Pro is a large-scale image model developed by Zhixiang Future, based on the native full-modal UiT architecture. With over 200 bytes of parameters, it sets state-of-the-art (SOTA) performance in tasks such as text-to-image rendering, text rendering, and instruction editing. The model integrates image pixels, text...

What is HiDream-O1-Image-Pro?

HiDream-O1-Image-Pro is a large-scale image model developed by IntelliJ IDEA based on the native multimodal architecture UiT. With over 200 bytes of parameters, it sets state-of-the-art (SOTA) performance in tasks such as text-to-image processing, text rendering, and instruction editing. The model integrates image pixels, text markers, and task conditions into a continuous shared label space, achieving deep fusion at the underlying level. The previous 8-byte open-source version topped the Artificial Analysis open-source leaderboard; the Pro version further validates the scalability of the native multimodal architecture, marking IntelliJ IDEA's step towards unified multimodal modeling.

Main functions of HiDream-O1-Image-Pro

  • General text imageIt supports the generation of high-quality, high-fidelity, and diverse images based on natural language descriptions, covering complex semantic understanding and visual scene construction.
  • High-fidelity text renderingIt accurately generates various text contents embedded in images, solving the industry pain point of text distortion and misalignment in traditional models.
  • Instructions for image editingIt supports users to make precise modifications to images through natural language commands, enabling flexible creative adjustments and content redrawing.
  • Multi-subject personalizationIn complex scenarios involving multiple subjects, maintain consistency in features and style among the subjects.
  • Diverse scene generationIt covers a variety of art styles and complex visual scenes, and has a powerful cross-domain generalization generation capability.

The technical principles of HiDream-O1-Image-Pro

  • Native full-modal architecture (UiT)It adopts the next-generation Unified Transformer architecture, fundamentally replacing the traditional U-Net and multi-module splicing coding paradigm.
  • Unified Continuous Shared Tag SpaceThe original image pixels, discrete text tags, and task conditions are uniformly mapped to the same continuous shared tag space for representation.
  • Underlying deep integration mechanismIt achieves deep integration of images, text, and multi-task conditions at the underlying representation level, rather than the traditional splicing process after separate encoding.
  • Breaking the bottleneck of modal separationIt solves the problems of insufficient complex semantic understanding, detail restoration and generalization ability caused by the separation of image and text encoding in the traditional LDM route.
  • Architectural scalability verificationFrom the 8B open-source version to the 200B+ closed-source version, it maintains leading performance, fully demonstrating the huge scalability of the native full-modal architecture.

How to use HiDream-O1-Image-Pro

There is currently no official access point for HiDream-O1-Image-Pro.

HiDream-O1-Image-Pro's core advantages

  • Native full-modal UiT architectureBased on Unified Transformer, image pixels, text tags and task conditions are uniformly incorporated into a continuous shared tag space to achieve deep fusion at the underlying level, which is not a traditional multi-module stitching.
  • 200B+ parameter scaleWith over 200 billion parameters, it sets a new state-of-the-art standard in tasks such as text-to-image processing, text rendering, command editing, and multi-subject personalization.
  • Architectural scalability verificationIt maintains leading performance from the 8B open-source version to the 200B+ closed-source version, proving that the native full-modal paradigm has powerful scaling capabilities.
  • High-fidelity text renderingIt accurately generates embedded text in images, solving the industry pain points of text distortion and misalignment in traditional diffusion models.
  • Any to Any cross-modal capabilityIt supports arbitrary modal input to arbitrary modal output, laying the foundation for the evolution to a world model.
  • Complex semantics and instruction complianceIts ability to understand and execute complex scene descriptions and editing instructions is significantly better than that of the traditional LDM route model.

Comparison of HiDream-O1-Image-Pro with similar competitors

Comparison Dimensions HiDream-O1-Image-Pro FLUX.2 [dev] Midjourney V7
Research and development Intelligent Future Black Forest Labs Midjourney
Underlying architecture UiT native full-modality Diffusion Transformer diffusion model
Parameter size 200B+ (closed source) / 8B (open source) Approximately 12B Not disclosed
Open source situation 8B Open Source / Pro Closed Source open source Closed source
Text rendering SOTA level excellent good
Core advantages Native full-modal unified modeling, Any to Any Rich open-source ecosystem and high-quality output Top-notch aesthetic quality and strong artistic style

Application Scenarios of HiDream-O1-Image-Pro

  • Business MarketingHiBurst AI generates high-quality product images and marketing materials for cross-border e-commerce and brand advertising, producing over one million e-commerce videos annually.
  • Film and television creationSupports cinematic-quality image generation and the entire process from creative concept to storyboarding to final production. The FramePan platform has produced over 5,000 minutes of short comics.
  • social media contentEmpowering the production of social media content such as short videos and graphic stories, vivago has reached over 40 million users in more than 100 countries and regions.
  • Advertising designPrecisely integrate visual elements with advertising copy to achieve high-fidelity advertising creative output that combines text and images.
  • IP OperationsIt assists in IP character design, style transfer, and cross-media content development, and supports maintaining consistency across multiple entities.