👏 Join our WeChat and Discord | 💻 Official website(官网) Try our model!    - **January 26, 2026**: 🚀 **HunyuanImage-3.0-Instruct-Distil** - Distilled checkpoint for efficient deployment (8 steps sampling recommended). - **January 26, 2026**: 🎉 **HunyuanImage-3.0-Instruct** - Release of **Instruct (with reasoning)** for intelligent prompt enhancement and **Image-to-Image** generation for creative editing. - **October 30, 2025**: 🚀 **HunyuanImage-3.0 vLLM Acceleration** - Significantly faster inference with vLLM support. - **September 28, 2025**: 📖 **HunyuanImage-3.0 Technical Report** - Comprehensive technical documentation now available. - **September 28, 2025**: 🎉 **HunyuanImage-3.0 Open Source** - Inference code and model weights publicly available. - HunyuanImage-3.0 (Image Generation Model) - [x] Inference - [x] HunyuanImage-3.0 Checkpoints - [x] HunyuanImage-3.0-Instruct Checkpoints (with reasoning) - [x] vLLM Support - [x] Distilled Checkpoints - [x] Image-to-Image Generation - [ ] Multi-turn Interaction
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🤗 HF Model | 💻 GitHub Repo | 📄 Paper > 📦 **Model layout.** This repository hosts **HunyuanOCR-1.5** checkpoint at the root (target base weights). The **DFlash speculative-decoding draft** lives under `dflash/`, and the previous **HunyuanOCR-1.0** is archived under `v1.0/` (load it with `subfolder="v1.0"`, or download the `v1.0/` directory directly). **HunyuanOCR-1.5** is a lightweight, end-to-end OCR-specialized vision-language model. It targets a broad range of text-centric visual tasks and unifies **document parsing, text spotting, information extraction, text-image translation** within a single end-to-end VLM.
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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HunyuanVideo
hunyuanvideo-community基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
HunyuanVideo-1.5-Diffusers-480p_i2v
hunyuanvideo-community基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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HunyuanVideo-1.5-Diffusers-480p_i2v_step_distilled
hunyuanvideo-community基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
HunyuanVideo-1.5-Diffusers-480p_t2v
hunyuanvideo-communityHunyuan1.5 use attention masks with variable-length sequences. For best performance, we recommend using an attention backend that handles padding efficiently. You can check our documentation to learn more about all the different attention backends we support.
HunyuanVideo-1.5-Diffusers-720p_i2v
hunyuanvideo-community基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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HunyuanVideo-1.5-Diffusers-720p_t2v
hunyuanvideo-communityHunyuan1.5 use attention masks with variable-length sequences. For best performance, we recommend using an attention backend that handles padding efficiently. We recommend installing kernels (`pip install kernels`) to access prebuilt attention kernels. You can check our documentation to learn more about all the different attention backends we support.
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We would like to thank the contributors to the Stable Diffusion, FLUX, diffusers, HuggingFace, Real-ESRGAN, ZIM, GroundingDINO, MoGe, Worldsheet, WorldGen repositories, for their open research.
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huper_recognizer
huper29基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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pdf-document-layout-analysis
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teknofest-2025-turkish-edu
Huseyin基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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tr-abdomen-rad-weights
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TEV-qwen3-coder-30B-A3B
husj576基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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