# DeepFloyd IF 根据 OpenAITools.app 于 2026-11-11 核对的流量数据，DeepFloyd IF（github.com）是一个收录在 Text to Image 下的 AI 平台，月访问量为 0，月度环比流量变化为 +0（0.0%）。其主要地理市场为全球（— 流量份额），采用免费定价模式。按月流量计算的主要竞争替代方案包括 MiniMax Image-01（525.37万次访问/月），Clipdrop（45.67万次访问/月），Stable Diffusion API（2.68万次访问/月）。 DeepFloyd IF is an open-source text-to-image model from DeepFloyd Lab at Stability AI that uses cascaded pixel diffusion for high photorealism and strong language understanding. ## 关键遥测与规格 | 指标 | 数值 | | :--- | :--- | | 工具名称 | DeepFloyd IF | | 标识 | deep-floyd | | Status | active | | Origin | open_source | | Maintenance | active | | 官方域名 | github.com | | 官网地址 | https://github.com/deep-floyd/IF | | 分类 | Text to Image, AI Image Generator, Open Source AI Models, AI Image Upscaler, AI 图像修补, Image to Image, AI GitHub | | 定价模式 | 免费 | | 月访问量 | 0 | | 月度环比流量变化 | 0 | | 月度环比增长率 | — | | 主要市场 | 全球 | | 市场份额 | — | | 直接访问量 | 0 | | 自然搜索访问 | 0 | | 社交访问 | 0 | | 推荐访问 | 0 | | 邮件访问 | 0 | | 评价得分 | 4.3 | | 收藏数 | 2 | | 支持平台 | 开源 | | 计费平台 | | | 属性 | 定价: 免费; 功能: 开源 | | 标签 | 文生图, 图像生成, 扩散模型, 超分辨率, 图像局部重绘, 照片级真实感, 开源, Hugging Face Diffusers | ## 概览 DeepFloyd IF is an open-source text-to-image model from DeepFloyd Lab at Stability AI that uses cascaded pixel diffusion for high photorealism and strong language understanding. ## 定价与套餐 Free and open source. The code is published on GitHub and the weights are available on Hugging Face; there is no paid plan, though you cover your own compute costs. ## 关键功能与能力 - **Cascaded diffusion pipeline:** IF splits generation into a 64px base model and two super-resolution stages for 256px and 1024px, letting users inspect each step. - **T5 text encoder:** A frozen T5 text encoder gives the model strong prompt adherence and language understanding compared with earlier models of its era. - **Multiple generation modes:** The model supports Dream-style generation, style transfer, super resolution, and inpainting workflows in notebooks. - **Diffusers integration:** IF is integrated into the Hugging Face Diffusers library, so you can run each stage individually with familiar tooling. ## 主要用例 - **Local image generation (AI developer):** Run IF locally to generate photorealistic images from text prompts with full control over each stage. - **Super resolution experiments (Research engineer):** Use the 256px and 1024px super-resolution stages to upscale or refine existing images. - **Style transfer and inpainting (Creative technologist):** Apply IF's style transfer and inpainting modes in notebooks for creative and editing projects. ## 优势 - High photorealism and strong prompt understanding for its generation - Fully open source with weights and code available - Integrated with the widely used Hugging Face Diffusers library - Granular cascade exposes each resolution stage for control ## 局限 - High VRAM requirements (16-24GB) for the full pipeline on local hardware - Original hosted Dream demo was retired, so you must run it yourself or use third-party hosts - Setup involves Python, Hugging Face login, and accepting model licence terms - Generation is relatively slow compared with newer single-stage models ## 常见问题 ### How do I run DeepFloyd IF? It is an open-source research release. You install it from the GitHub repository or via Hugging Face Diffusers and run it on your own GPU hardware. ### What hardware do I need? The recommended setup is roughly 16GB of VRAM for the base module and first upscaler, and around 24GB to run the base plus both super-resolution stages, though Diffusers CPU offloading can reduce this. ### How does the cascade actually work? DeepFloyd IF generates 64px images in the base stage and then upscales to 256px and 1024px through two super-resolution models, rather than generating at full resolution in one pass. ### Is DeepFloyd IF free to use? Yes. IF is distributed freely under its model licence and is integrated into the Hugging Face Diffusers library. ### DeepFloyd IF 的月流量和增长趋势如何？ DeepFloyd IF 目前每月获得 0 访问量，月度环比流量变化为 +0（增长率 0.0%）。其主要来源市场是全球（— 份额），包括每月 0 次直接访问和每月 0 次自然搜索访问。 ### DeepFloyd IF 免费吗？它的定价模式是什么？ DeepFloyd IF 采用免费定价模式。Free and open source. The code is published on GitHub and the weights are available on Hugging Face; there is no paid plan, though you cover your own compute costs. 支持的计费和结账平台包括：未列出。 ### 2026 年 DeepFloyd IF 的最佳替代方案有哪些？ 基于 OpenAITools.app 的分类流量和功能契合度，DeepFloyd IF 的前五个替代方案是：1. MiniMax Image-01（525.37万次访问/月）; 2. Clipdrop（45.67万次访问/月）; 3. Stable Diffusion API（2.68万次访问/月）; 4. ImgGen AI（14.84万次访问/月）; 5. Stable Diffusion（Stability AI）（34.19万次访问/月）。 ### DeepFloyd IF 支持哪些平台和核心 AI 能力？ DeepFloyd IF 被归类在 Text to Image, AI Image Generator, Open Source AI Models, AI Image Upscaler 下，支持以下平台：开源，其核心能力标签包括：文生图, 图像生成, 扩散模型, 超分辨率, 图像局部重绘, 照片级真实感。 ## 替代工具 | 工具名称 | 月访问量 | 定价模式 | 对比 | | :--- | :--- | :--- | :--- | | [MiniMax Image-01](https://openaitools.app/zh/tool/minimax-image-01) | 5,253,734 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-minimax-image-01) | | [Clipdrop](https://openaitools.app/zh/tool/clipdrop) | 456,718 | 免费增值，定价请咨询 | [对比](https://openaitools.app/zh/compare/clipdrop-vs-deep-floyd) | | [Stable Diffusion API](https://openaitools.app/zh/tool/stablediffusion-api) | 26,802 | 付费 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-stablediffusion-api) | | [ImgGen AI](https://openaitools.app/zh/tool/imggen-ai) | 148,444 | 免费 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-imggen-ai) | | [Stable Diffusion（Stability AI）](https://openaitools.app/zh/tool/stable-diffusion) | 341,872 | 免费增值，定价请咨询 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-stable-diffusion) | | [Stable Horde](https://openaitools.app/zh/tool/stable-horde) | 103,752 | 免费 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-stable-horde) | | [Magnific AI](https://openaitools.app/zh/tool/magnific-ai) | 39,873 | Free, Subscription, Enterprise | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-magnific-ai) | | [Bagel](https://openaitools.app/zh/tool/bagel) | 7,329 | 免费 | [对比](https://openaitools.app/zh/compare/bagel-vs-deep-floyd) | | [Ideogram](https://openaitools.app/zh/tool/ideogram) | 1,882,585 | 免费增值 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-ideogram) | | [Unsloth AI](https://openaitools.app/zh/tool/unsloth-ai) | 887,457 | 免费 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-unsloth-ai) | | [ArtSmart.ai](https://openaitools.app/zh/tool/artsmart-ai) | 30,781 | 付费 | [对比](https://openaitools.app/zh/compare/artsmart-ai-vs-deep-floyd) | | [ImaginePro](https://openaitools.app/zh/tool/imaginepro) | 10,348 | 免费增值，免费试用，付费 | [对比](https://openaitools.app/zh/compare/deep-floyd-vs-imaginepro) | --- 来源：https://openaitools.app/zh/tool/deep-floyd