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Introducing Frames: An image generation model offering unprecedented stylistic control. Frames is our newest foundation model for image generation, marking a big step forward in stylistic control and visual fidelity. With Frames, you can begin to architect worlds that represent very specific points of view and aesthetic characteristics. See...

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Frames allows you to design with precision the look, feel and atmosphere of the world you want to create. World 3190: 1980s SFX Makeup (2/11)

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World 3204: 1970s Album Art (3/11)

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World 4027: Japanese Zine (4/11)

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World 7621: Digital Picture Profiles (5/11)

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World 0981: Dynamic Range Landscapes (6/11)

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World 8421: Disposables (7/11)

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World 1009: Still Life (8/11)

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World 8862: Magazine Collage (9/11)

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World 3107: Objects in Motion (10/11)

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We're gradually rolling out access inside Gen-3 Alpha to allow you to build more of your worlds within a larger, more seamless creative flow. Learn more: (11/11)

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We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

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