[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-6755":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":15,"compositeScore":18,"rankGlobal":9,"rankLanguage":9,"license":19,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":22,"hasPages":20,"topics":23,"createdAt":9,"pushedAt":9,"updatedAt":33,"readmeContent":34,"aiSummary":35,"trendingCount":15,"starSnapshotCount":15,"syncStatus":36,"lastSyncTime":37,"discoverSource":38},6755,"MochiDiffusion","MochiDiffusion\u002FMochiDiffusion","Run Stable Diffusion on Mac natively","",null,"Swift",7892,362,60,3,0,1,8,38.68,"GNU General Public License v3.0",false,"main",true,[24,25,26,27,28,29,30,31,32],"ane","apple","apple-silicon","coreml","macos","neural-engine","stable-diffusion","swift","swiftui","2026-06-12 02:01:29","\u003Cp align=\"center\">\n\u003Cimg height=\"256\" src=\"https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fraw\u002Fmain\u002FMochi Diffusion\u002FResources\u002FAssets.xcassets\u002FAppIcon.appiconset\u002FAppIcon.png\" \u002F>\n\u003C\u002Fp>\n\n\u003Ch1 align=\"center\">Mochi Diffusion\u003C\u002Fh1>\n\n\u003Cp align=\"center\">Run Stable Diffusion and FLUX.2 Klein on Mac natively\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fblob\u002Fmain\u002FREADME.md\">English\u003C\u002Fa>,\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fblob\u002Fmain\u002FREADME.ko.md\">한국어\u003C\u002Fa>,\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fblob\u002Fmain\u002FREADME.zh-Hans.md\">中文\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n\u003Ca title=\"Discord\" target=\"_blank\" href=\"https:\u002F\u002Fdiscord.gg\u002Fx2kartzxGv\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fdiscord\u002F1068185566782423092?color=blueviolet&label=discord\">\u003C\u002Fa>\n\u003Ca title=\"Crowdin\" target=\"_blank\" href=\"https:\u002F\u002Fcrowdin.com\u002Fproject\u002Fmochi-diffusion\">\u003Cimg src=\"https:\u002F\u002Fbadges.crowdin.net\u002Fmochi-diffusion\u002Flocalized.svg\">\u003C\u002Fa>\n\u003Ca title=\"License\" target=\"_blank\" href=\"https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fblob\u002Fmain\u002FLICENSE\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002FMochiDiffusion\u002FMochiDiffusion?color=blue\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n![Screenshot](.github\u002Fimages\u002Fscreenshot.png)\n\n## Features\n\n- [Apple's Core ML Stable Diffusion implementation](https:\u002F\u002Fgithub.com\u002Fapple\u002Fml-stable-diffusion) to achieve maximum performance and speed on Apple Silicon based Macs while reducing memory requirements\n- Extremely fast and memory efficient (~150MB with Neural Engine)\n- Runs well on all Apple Silicon Macs by fully utilizing Neural Engine\n- Generate images locally and completely offline\n- Generate images based on an existing image (commonly known as Image2Image)\n- Generate images using ControlNet\n- Generated images are saved with prompt info inside EXIF metadata (view in Finder's Get Info window)\n- Built-in gallery with import\u002Fsave\u002Fsync support\n- Use custom Stable Diffusion Core ML models\n- No worries about pickled models\n- macOS native app using SwiftUI\n- [Iris](https:\u002F\u002Fgithub.com\u002Fantirez\u002Firis.c) FLUX.2 (Klein) pipeline support\n\n## Downloads\n\n[Latest version](https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Freleases)\n\n[Community models](https:\u002F\u002Fhuggingface.co\u002Fcoreml-community#models)\n\n[ControlNet models](https:\u002F\u002Fhuggingface.co\u002Fcoreml-community\u002FControlNet-Models-For-Core-ML\u002Ftree\u002Fmain\u002FCN)\n\n[Stable Diffusion 1.5 with ControlNet](https:\u002F\u002Fhuggingface.co\u002Fcoreml-community\u002Fcoreml-stable-diffusion-v1-5_cn\u002Ftree\u002Fmain\u002Fsplit_einsum)\n\n[FLUX.2-klein-4B (distilled)](https:\u002F\u002Fhuggingface.co\u002Fblack-forest-labs\u002FFLUX.2-klein-4B)\n\n[FLUX.2-klein-9B (distilled)](https:\u002F\u002Fhuggingface.co\u002Fblack-forest-labs\u002FFLUX.2-klein-9B)\n\nWhen using a model for the very first time, it may take up to 2 minutes for the Neural Engine to compile a cached version. Afterwards, subsequent generations will be much faster.\n\n## Compute Unit\n\n- `CPU & Neural Engine` provides a good balance between speed and low memory usage\n- `CPU & GPU` may be faster on M1 Max, Ultra and later but will use more memory\n\nDepending on the option chosen, you will need to use the correct model version (see Models section for details).\n\n## Models\n\nYou will need Core ML Stable Diffusion or FLUX.2 Klein models in order to use Mochi Diffusion.\n\n### Core ML Stable Diffusion\n\n1. [Convert](https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fwiki\u002FHow-to-convert-Stable-Diffusion-models-to-Core-ML) or download Core ML models\n    - `split_einsum` version is compatible with all compute unit options including Neural Engine\n    - `original` version is only compatible with `CPU & GPU` option\n2. By default, the app's model folder will be created under your home directory. This location can be customized under Settings\n3. In the model folder, create a new folder with the name you'd like displayed in the app then move or extract the converted models here\n4. Your directory structure should look like this:\n```\n\u003CHome Directory>\u002F\n└── MochiDiffusion\u002F\n    └── models\u002F\n        ├── stable-diffusion-2-1_split-einsum_compiled\u002F\n        │   ├── merges.txt\n        │   ├── TextEncoder.mlmodelc\n        │   ├── Unet.mlmodelc\n        │   ├── VAEDecoder.mlmodelc\n        │   ├── VAEEncoder.mlmodelc\n        │   └── vocab.json\n        ├── ...\n        └── ...\n```\n\n### FLUX.2 Klein\n\nNo conversion is required for FLUX.2 Klein models.\n\n1. Download the text_encode, tokenizer, transformer, and vae for a FLUX.2 Klein model from the [Downloads](#downloads) links above (or use [`download_model.sh`](https:\u002F\u002Fgithub.com\u002Fantirez\u002Firis.c\u002Fblob\u002Fmain\u002Fdownload_model.sh))\n2. Place in MochiDiffusion's model folder\n3. Your directory structure should look like this:\n```\n\u003CHome Directory>\u002F\n└── MochiDiffusion\u002F\n    └── models\u002F\n        ├── flux-klein-4b\u002F\n        │   ├── text_encoder\u002F\n        │   ├── tokenizer\u002F\n        │   ├── transformer\u002F\n        │   └── vae\u002F\n        ├── ...\n        └── ...        \n```\n(see [iris.c issue #12](https:\u002F\u002Fgithub.com\u002Fantirez\u002Firis.c\u002Fissues\u002F12)) for specific guidance for flux-klein-4b)\n\n## Compatibility\n\n- Apple Silicon (M1 and later)\n- macOS 15.6 and later\n- Xcode 26.0 or later (to build)\n\n## Privacy\n\nAll generation happens locally and absolutely nothing is sent to the cloud.\n\n## Contributing\n\nMochi Diffusion is always looking for contributions, whether it's through bug reports, code, or new translations.\n\n- If you find a bug, or would like to suggest a new feature or enhancement, try [searching for your problem first](https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fissues) as it helps avoid duplicates. If you can't find your issue, feel free to [create a new issue](https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fissues\u002Fnew\u002Fchoose). Don't create an issue for your question as those are for bugs and feature requests only.\n\n- If you're looking to contribute code, feel free to [open a Pull Request](https:\u002F\u002Fgithub.com\u002FMochiDiffusion\u002FMochiDiffusion\u002Fpulls). I recommend installing [swift-format](https:\u002F\u002Fgithub.com\u002Fapple\u002Fswift-format#getting-swift-format) to catch lint issues.\n\n- If you'd like to translate Mochi Diffusion to your language, please visit the [project page on Crowdin](https:\u002F\u002Fcrowdin.com\u002Fproject\u002Fmochi-diffusion). You can create an account for free and start translating and\u002For approving.\n\n## Credits\n\n- [Apple's Core ML Stable Diffusion implementation](https:\u002F\u002Fgithub.com\u002Fapple\u002Fml-stable-diffusion)\n- [iris.c](https:\u002F\u002Fgithub.com\u002Fantirez\u002Firis.c)\n- [Hugging Face's Swift UI sample implementation](https:\u002F\u002Fgithub.com\u002Fhuggingface\u002Fswift-coreml-diffusers)\n- App Icon by [Zabriskije](https:\u002F\u002Fgithub.com\u002FZabriskije)\n","Mochi Diffusion 是一个能够在 Mac 上原生运行 Stable Diffusion 和 FLUX.2 Klein 的项目。该项目利用了 Apple 的 Core ML 实现，以最大化苹果芯片 Mac 的性能和速度，同时减少内存需求。它具有极高的运行效率与内存利用率（使用 Neural Engine 时约 150MB），支持基于现有图像生成新图像、使用 ControlNet 生成图像等功能，并且生成的图片会保存带有提示信息的 EXIF 元数据。此外，Mochi Diffusion 提供了一个内置画廊，支持导入、保存及同步功能，并允许用户使用自定义的 Stable Diffusion Core ML 模型。此应用非常适合于需要在 macOS 系统下离线创作艺术作品的设计者或艺术家使用。",2,"2026-06-11 03:08:42","top_language"]