# tencent-hunyuan/hunyuanimage-3.0 **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/tencent-hunyuan-hunyuanimage-3-0).** 2,862 stars · 143 forks · Python · other ## Links - GitHub: https://github.com/Tencent-Hunyuan/HunyuanImage-3.0 - Homepage: https://hunyuan.tencent.com/image - awesome-repositories: https://awesome-repositories.com/repository/tencent-hunyuan-hunyuanimage-3-0.md ## Topics `image-generation` `native-multimodal-model` ## Description HunyuanImage-3.0 is a diffusion-based text-to-image tool and large language model image generator designed for creating high-fidelity, photorealistic visual content. It functions as an image-to-image synthesis framework and a multimodal visual reasoning engine. The system includes a prompt refinement system that automatically rewrites sparse user inputs into detailed descriptions to improve output precision. It also employs a reasoning chain architecture to analyze image inputs and prompts, decomposing complex editing tasks into structured sub-tasks. The project covers a range of synthesis capabilities, including image fusion, reference-based synthesis for style modification or background replacement, and AI image compositing to merge multiple source images into a single coherent scene. ## Tags ### Artificial Intelligence & ML - [Image Diffusion Models](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-systems/image-diffusion-models.md) — Provides a core diffusion-based system that iteratively removes noise to create photorealistic images from guidance. - [Language Model Prompt Rewriters](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-prompt-configurations/prompt-evaluation-tools/prompt-refinement-utilities/language-model-prompt-rewriters.md) — Uses a language model to rewrite sparse user inputs into detailed descriptions for better visual alignment. - [Text-to-Image Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-image-generators.md) — Produces high-fidelity photorealistic imagery from natural language prompts using a diffusion pipeline. ([source](https://cdn.jsdelivr.net/gh/tencent-hunyuan/hunyuanimage-3.0@main/README.md)) - [Image Generation Models](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation-models.md) — Functions as an LLM-based image generator creating photorealistic visuals from natural language prompts. - [Image-to-Image Synthesis Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/image-to-image-synthesis-frameworks.md) — Provides a framework for merging multiple source images and using reference files for style modification. - [Multimodal Reasoning Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/multimodal-reasoning-engines.md) — Implements a reasoning chain architecture that analyzes image inputs and prompts to decompose editing tasks. - [Reasoning Chains](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-chains.md) — Employs a reasoning-chain architecture to decompose complex image editing requests into structured sub-tasks. - [Visual Prompt Enhancers](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-models/reasoning-pipelines/visual-prompt-enhancers.md) — Refines sparse or vague user inputs into detailed visual descriptions using a reasoning-driven pipeline. ([source](https://cdn.jsdelivr.net/gh/tencent-hunyuan/hunyuanimage-3.0@main/README.md)) - [Visual Reasoning Services](https://awesome-repositories.com/f/artificial-intelligence-ml/visual-reasoning-services.md) — Analyzes images and prompts through a structured reasoning chain to execute complex editing tasks. - [Task Decomposition](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/orchestration-engines/ai-agent/reasoning-action-loops/visual-reasoning/task-decomposition.md) — Decomposes complex editing tasks into structured visual components via a reasoning chain. ([source](https://cdn.jsdelivr.net/gh/tencent-hunyuan/hunyuanimage-3.0@main/README.md)) - [Multimodal Embeddings](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-models/latent-space-generative-models/shared-latent-spaces/multimodal-embeddings.md) — Maps text prompts and visual references into a shared numerical space for precise semantic blending. - [Cross-Attention Conditioning](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-video-generators/cross-attention-conditioning.md) — Uses cross-attention mechanisms to align text tokens with specific spatial regions during the image generation process. - [Reference-Conditioned Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation/reference-conditioned-generation.md) — Generates new images by combining text prompts with reference files to modify styles or replace backgrounds. ([source](https://cdn.jsdelivr.net/gh/tencent-hunyuan/hunyuanimage-3.0@main/README.md)) - [Style Transfers](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation/style-transfers.md) — Extracts aesthetic and structural features from reference images to constrain the output style. - [Cascaded Upscaling Models](https://awesome-repositories.com/f/artificial-intelligence-ml/neural-network-architectures/u-net-architectures/cascaded-upscaling-models.md) — Implements a multi-stage pipeline that progressively refines low-resolution seeds into high-fidelity visual outputs. - [Visual Reference Prompting](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-models/reasoning-pipelines/visual-prompt-enhancers/visual-reference-prompting.md) — Uses reference images to guide the model's output for style modification and background replacement. ### Graphics & Multimedia - [Composite Image Generation](https://awesome-repositories.com/f/graphics-multimedia/composite-image-generation.md) — Combines visual elements from multiple source images into a single coherent composite scene. ([source](https://cdn.jsdelivr.net/gh/tencent-hunyuan/hunyuanimage-3.0@main/README.md))