[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72664":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":25,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":36,"readmeContent":37,"aiSummary":38,"trendingCount":16,"starSnapshotCount":16,"syncStatus":39,"lastSyncTime":40,"discoverSource":41},72664,"llamafile","mozilla-ai\u002Fllamafile","mozilla-ai","Distribute and run LLMs with a single file.","https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile",null,"C++",24853,1387,201,189,0,177,269,433,531,119.43,"Other",false,"main",true,[27,28,29,30,31,32,33,34,35],"cross-platform","gguf","llama-cpp","local-ai","local-inference","local-llm","open-source-ai","single-file-executable","speech-to-text","2026-06-12 04:01:06","# llamafile\n\n\u003Cimg src=\"docs\u002Fimages\u002Fllamafile-640x640.png\" width=\"320\" height=\"320\"\n     alt=\"[line drawing of llama animal head in front of slightly open manilla folder filled with files]\">\n\n[![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-Apache%202.0-blue.svg)](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Fblob\u002Fmain\u002FLICENSE)\n[![ci status](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Factions\u002Fworkflows\u002Fci.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Factions\u002Fworkflows\u002Fci.yml)\n[![Based on llama.cpp](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fllama.cpp-7f5ee54-orange.svg)](https:\u002F\u002Fgithub.com\u002Fggml-org\u002Fllama.cpp\u002Fcommit\u002F7f5ee54)\n[![Based on whisper.cpp](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fwhisper.cpp-2eeeba5-green.svg)](https:\u002F\u002Fgithub.com\u002Fggml-org\u002Fwhisper.cpp\u002Fcommit\u002F2eeeba5)\n[![Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FYuMNeuKStr?style=flat)](https:\u002F\u002Fdiscord.gg\u002FYuMNeuKStr)\n[![Mozilla Builders](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBuilders-6E6E6E?logo=mozilla&logoColor=white&labelColor=4A4A4A)](https:\u002F\u002Fbuilders.mozilla.org\u002F)\n\n**llamafile lets you distribute and run LLMs with a single file.**\n\nllamafile is a [Mozilla Builders](https:\u002F\u002Fbuilders.mozilla.org\u002F) project (see its [announcement blog post](https:\u002F\u002Fhacks.mozilla.org\u002F2023\u002F11\u002Fintroducing-llamafile\u002F)), now revamped by [Mozilla.ai](https:\u002F\u002Fwww.mozilla.ai\u002Fopen-tools\u002Fllamafile). \n\nOur goal is to make open LLMs much more\naccessible to both developers and end users. We're doing that by\ncombining [llama.cpp](https:\u002F\u002Fgithub.com\u002Fggerganov\u002Fllama.cpp) with [Cosmopolitan Libc](https:\u002F\u002Fgithub.com\u002Fjart\u002Fcosmopolitan) into one\nframework that collapses all the complexity of LLMs down to\na single-file executable (called a \"llamafile\") that runs\nlocally on most operating systems and CPU archiectures, with no installation.\n\nllamafile also includes **[whisperfile](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fwhisperfile)**, a single-file speech-to-text tool built on [whisper.cpp](https:\u002F\u002Fgithub.com\u002Fggerganov\u002Fwhisper.cpp) and the same Cosmopolitan packaging. It supports transcription and translation of audio files across all the same platforms, with no installation required.\n\n\n## v0.10.*\n\n**llamafile versions starting from 0.10.0 use a new build system**, aimed at keeping our code more easily \naligned with the latest versions of llama.cpp. This means they support more recent models and functionalities,\nbut at the same time they might be missing some of\nthe features you were accustomed to (check out [this doc](README_0.10.0.md) for a high-level description of what has been done). If you liked\nthe \"classic experience\" more, you will always be able to access the previous versions from our\n[releases](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Freleases) page. Our pre-built llamafiles always\nshow which version of the server they have been bundled with ([0.9.* example](https:\u002F\u002Fhuggingface.co\u002Fmozilla-ai\u002Fllava-v1.5-7b-llamafile), [0.10.* example](https:\u002F\u002Fhuggingface.co\u002Fmozilla-ai\u002Fllamafile_0.10)), so you will always know\nwhich version of the software you are downloading.\n\n\n> **We want to hear from you!**\nWhether you are a new user or a long-time fan, please share what you find most valuable about llamafile and what would make it more useful for you.\n[Read more via the blog](https:\u002F\u002Fblog.mozilla.ai\u002Fllamafile-returns\u002F) and add your voice to the discussion [here](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Fdiscussions\u002F809).\n\n\n## Quick Start\n\nDownload and run your first llamafile in minutes:\n\n```sh\n# Download an example model (Qwen3.5 0.8B)\ncurl -LO https:\u002F\u002Fhuggingface.co\u002Fmozilla-ai\u002Fllamafile_0.10\u002Fresolve\u002Fmain\u002FQwen3.5-0.8B-Q8_0.llamafile\n\n# Make it executable (macOS\u002FLinux\u002FBSD)\nchmod +x Qwen3.5-0.8B-Q8_0.llamafile\n\n# Run it\n.\u002FQwen3.5-0.8B-Q8_0.llamafile\n```\n\nWe chose this model because that's the smallest one we have\nbuilt a llamafile for, so most likely to work out-of-the-box for you.\nIf you have powerful hardware and\u002For GPUs, [feel free to choose](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fgetting-started\u002Fexample_llamafiles)\nlarger and more expressive models which should provide more accurate\nresponses.\n\n**Windows users:** Rename the file to add `.exe` extension before running.\n\n**Note - Only executables under 4GB can run on Windows, so any llamafile above 4GB won't work. Download the [llamafile](https:\u002F\u002Fgithub.com\u002Fmozilla-ai\u002Fllamafile\u002Freleases) binary and run it with any [external weights\u002Fmodels(GGUF)](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fgetting-started\u002Fquickstart#using-llamafile-with-external-weights).**\n\n## Documentation\n\nCheck the full documentation at [docs.mozilla.ai\u002Fllamafile](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile), or directly jump into one of the following subsections:\n\n- [Quickstart](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fgetting-started\u002Fquickstart)\n- [Example llamafiles](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fgetting-started\u002Fexample_llamafiles)\n- [Running a llamafile](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fusing-llamafile\u002Frunning_llamafile)\n- [Creating llamafiles](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fusing-llamafile\u002Fcreating_llamafiles)\n- [Source installation](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fusing-llamafile\u002Fsource_installation)\n- [Technical details](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Freference\u002Ftechnical_details)\n- [Supported Systems](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Freference\u002Fsupport)\n- [Troubleshooting](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Freference\u002Ftroubleshooting)\n- [Whisperfile](https:\u002F\u002Fdocs.mozilla.ai\u002Fllamafile\u002Fwhisperfile)\n\n\n## Licensing\n\nWhile the llamafile project is Apache 2.0-licensed, our changes\nto llama.cpp and whisper.cpp are licensed under MIT (just like the projects\nthemselves) so as to remain compatible and upstreamable in the future,\nshould that be desired.\n\nThe llamafile logo on this page was generated with the assistance of DALL·E 3.\n\n\n[![Star History Chart](https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=Mozilla-Ocho\u002Fllamafile&type=Date)](https:\u002F\u002Fstar-history.com\u002F#Mozilla-Ocho\u002Fllamafile&Date)\n","llamafile 是一个用于分发和运行大语言模型（LLM）的单文件解决方案。该项目基于 llama.cpp 和 Cosmopolitan Libc，将复杂的 LLM 功能整合到一个可执行文件中，无需额外安装即可在多种操作系统和 CPU 架构上本地运行。此外，它还包含了 whisperfile，这是一个基于 whisper.cpp 的单文件语音转文字工具，支持音频文件的转录与翻译。llamafile 适用于需要简化 LLM 部署流程、提高模型可用性的开发者和终端用户场景，特别是在跨平台环境中希望减少依赖管理的情况下。",2,"2026-06-11 03:43:04","high_star"]