# DeepFloyd IF 依據 OpenAITools.app 於 2026-11-11 查驗的觀測資料，DeepFloyd IF（github.com）是收錄於 Text to Image 的 AI 平台，每月產生 0 次造訪，月流量變化量為 +0（0.0%）。其主要地理市場為全球（流量佔比 —），並採用免費定價模式。依每月流量計算的主要競爭替代方案包括 MiniMax Image-01（每月 525.37萬次造訪），Clipdrop（每月 45.67萬次造訪），Stable Diffusion API（每月 2.68萬次造訪）。 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. ## 主要觀測資料與規格 | 指標 | 數值 | | :--- | :--- | | 工具名稱 | DeepFloyd IF | | 代稱 | deep-floyd | | Status | active | | Origin | open_source | | Maintenance | active | | 官方網域 | github.com | | 網站網址 | https://github.com/deep-floyd/IF | | 分類 | Text to Image, AI 圖像生成器, 開源 AI 模型, AI 影像放大工具, AI 影像修補, 圖生圖, AI GitHub | | 定價模式 | 免費 | | 每月造訪次數 | 0 | | 月流量變化 | 0 | | 月成長率 | — | | 主要市場 | 全球 | | 市佔率 | — | | 直接造訪 | 0 | | 自然搜尋造訪 | 0 | | 社群造訪 | 0 | | 推薦流量造訪 | 0 | | 電子郵件造訪 | 0 | | 評論分數 | 4.3 | | 收藏數 | 2 | | 支援平台 | 開源 | | 帳務平台 | | | 屬性 | 價格: 免費; 功能: 開源 | | 標籤 | 文生圖, 影像生成, 擴散模型, 超解析度, 影像局部重繪, 照片級真實感, 開源, Hugging Face Diffusers | ## 總覽 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. ## 價格與方案 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. ## 關鍵功能與能力 - **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. ## 主要使用情境 - **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. ## 優勢 - 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 ## 限制 - 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 ## 常見問題 ### 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 的每月流量與成長趨勢為何？ DeepFloyd IF 目前每月有 0 次造訪，月流量變化為 +0（成長率 0.0%）。其主要來源市場為全球（佔比 —），其中包含每月 0 次直接造訪與每月 0 次自然搜尋造訪。 ### DeepFloyd IF 是免費的嗎？其定價模式為何？ DeepFloyd IF 採用免費定價模式。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. 支援的帳務與結帳平台包括：未列出。 ### 2026 年最佳的 DeepFloyd IF 替代方案有哪些？ 依據 OpenAITools.app 的分類流量與功能契合度，DeepFloyd IF 的前五大替代方案為：1. MiniMax Image-01（每月 525.37萬次造訪）; 2. Clipdrop（每月 45.67萬次造訪）; 3. Stable Diffusion API（每月 2.68萬次造訪）; 4. ImgGen AI（每月 14.84萬次造訪）; 5. Stable Diffusion（Stability AI）（每月 34.19萬次造訪）。 ### DeepFloyd IF 支援哪些平台與核心 AI 能力？ DeepFloyd IF 分類於 Text to Image, AI 圖像生成器, 開源 AI 模型, AI 影像放大工具，支援以下平台：開源，其核心能力標籤包括：文生圖, 影像生成, 擴散模型, 超解析度, 影像局部重繪, 照片級真實感。 ## 替代方案 | 工具名稱 | 每月造訪次數 | 定價模式 | 比較 | | :--- | :--- | :--- | :--- | | [MiniMax Image-01](https://openaitools.app/tw/tool/minimax-image-01) | 5,253,734 | 需聯絡報價 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-minimax-image-01) | | [Clipdrop](https://openaitools.app/tw/tool/clipdrop) | 456,718 | 免費增值、需聯絡報價 | [比較](https://openaitools.app/tw/compare/clipdrop-vs-deep-floyd) | | [Stable Diffusion API](https://openaitools.app/tw/tool/stablediffusion-api) | 26,802 | 付費 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-stablediffusion-api) | | [ImgGen AI](https://openaitools.app/tw/tool/imggen-ai) | 148,444 | 免費 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-imggen-ai) | | [Stable Diffusion（Stability AI）](https://openaitools.app/tw/tool/stable-diffusion) | 341,872 | 免費增值、需聯絡報價 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-stable-diffusion) | | [Stable Horde](https://openaitools.app/tw/tool/stable-horde) | 103,752 | 免費 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-stable-horde) | | [Magnific AI](https://openaitools.app/tw/tool/magnific-ai) | 39,873 | Free, Subscription, Enterprise | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-magnific-ai) | | [Bagel](https://openaitools.app/tw/tool/bagel) | 7,329 | 免費 | [比較](https://openaitools.app/tw/compare/bagel-vs-deep-floyd) | | [Ideogram](https://openaitools.app/tw/tool/ideogram) | 1,882,585 | 免費增值 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-ideogram) | | [Unsloth AI](https://openaitools.app/tw/tool/unsloth-ai) | 887,457 | 免費 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-unsloth-ai) | | [ArtSmart.ai](https://openaitools.app/tw/tool/artsmart-ai) | 30,781 | 付費 | [比較](https://openaitools.app/tw/compare/artsmart-ai-vs-deep-floyd) | | [ImaginePro](https://openaitools.app/tw/tool/imaginepro) | 10,348 | 免費增值、免費試用、付費 | [比較](https://openaitools.app/tw/compare/deep-floyd-vs-imaginepro) | --- 來源：https://openaitools.app/tw/tool/deep-floyd