[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-405":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":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":29,"readmeContent":30,"aiSummary":31,"trendingCount":16,"starSnapshotCount":16,"syncStatus":17,"lastSyncTime":32,"discoverSource":33},405,"gpt4all","nomic-ai\u002Fgpt4all","nomic-ai","GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.","https:\u002F\u002Fnomic.ai\u002Fgpt4all",null,"C++",77377,8318,700,724,0,2,26,51,17,72.1,"MIT License",false,"main",true,[27,28],"ai-chat","llm-inference","2026-06-17 04:00:03","\u003Ch1 align=\"center\">GPT4All\u003C\u002Fh1>\n\n\u003Cp align=\"center\">\n  Now with support for DeepSeek R1 Distillations\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fwww.nomic.ai\u002Fgpt4all\">Website\u003C\u002Fa> • \u003Ca href=\"https:\u002F\u002Fdocs.gpt4all.io\">Documentation\u003C\u002Fa> • \u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002FmGZE39AS3e\">Discord\u003C\u002Fa> • \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=gQcZDXRVJok\">YouTube Tutorial\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.\n\u003C\u002Fp>\n\u003Cp align=\"center\">\n  No API calls or GPUs required - you can just download the application and \u003Ca href=\"https:\u002F\u002Fdocs.gpt4all.io\u002Fgpt4all_desktop\u002Fquickstart.html#quickstart\">get started\u003C\u002Fa>.\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  Read about what's new in \u003Ca href=\"https:\u002F\u002Fwww.nomic.ai\u002Fblog\u002Ftag\u002Fgpt4all\">our blog\u003C\u002Fa>.\n\u003C\u002Fp>\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fnomic.ai\u002Fgpt4all\u002F#newsletter-form\">Subscribe to the newsletter\u003C\u002Fa>\n\u003C\u002Fp>\n\nhttps:\u002F\u002Fgithub.com\u002Fnomic-ai\u002Fgpt4all\u002Fassets\u002F70534565\u002F513a0f15-4964-4109-89e4-4f9a9011f311\n\n\u003Cp align=\"center\">\nGPT4All is made possible by our compute partner \u003Ca href=\"https:\u002F\u002Fwww.paperspace.com\u002F\">Paperspace\u003C\u002Fa>.\n\u003C\u002Fp>\n\n## Download Links\n\n\u003Cp>\n  — \u003Ca href=\"https:\u002F\u002Fgpt4all.io\u002Finstallers\u002Fgpt4all-installer-win64.exe\">\n    \u003Cimg src=\"gpt4all-bindings\u002Fpython\u002Fdocs\u002Fassets\u002Fwindows.png\" style=\"height: 1em; width: auto\" \u002F> Windows Installer\n  \u003C\u002Fa> —\n\u003C\u002Fp>\n\u003Cp>\n  — \u003Ca href=\"https:\u002F\u002Fgpt4all.io\u002Finstallers\u002Fgpt4all-installer-win64-arm.exe\">\n    \u003Cimg src=\"gpt4all-bindings\u002Fpython\u002Fdocs\u002Fassets\u002Fwindows.png\" style=\"height: 1em; width: auto\" \u002F> Windows ARM Installer\n  \u003C\u002Fa> —\n\u003C\u002Fp>\n\u003Cp>\n  — \u003Ca href=\"https:\u002F\u002Fgpt4all.io\u002Finstallers\u002Fgpt4all-installer-darwin.dmg\">\n    \u003Cimg src=\"gpt4all-bindings\u002Fpython\u002Fdocs\u002Fassets\u002Fmac.png\" style=\"height: 1em; width: auto\" \u002F> macOS Installer\n  \u003C\u002Fa> —\n\u003C\u002Fp>\n\u003Cp>\n  — \u003Ca href=\"https:\u002F\u002Fgpt4all.io\u002Finstallers\u002Fgpt4all-installer-linux.run\">\n    \u003Cimg src=\"gpt4all-bindings\u002Fpython\u002Fdocs\u002Fassets\u002Fubuntu.svg\" style=\"height: 1em; width: auto\" \u002F> Ubuntu Installer\n  \u003C\u002Fa> —\n\u003C\u002Fp>\n\u003Cp>\n  The Windows and Linux builds require Intel Core i3 2nd Gen \u002F AMD Bulldozer, or better.\n\u003C\u002Fp>\n\u003Cp>\n  The Windows ARM build supports Qualcomm Snapdragon and Microsoft SQ1\u002FSQ2 processors.\n\u003C\u002Fp>\n\u003Cp>\n  The Linux build is x86-64 only (no ARM).\n\u003C\u002Fp>\n\u003Cp>\n  The macOS build requires Monterey 12.6 or newer. Best results with Apple Silicon M-series processors.\n\u003C\u002Fp>\n\nSee the full [System Requirements](gpt4all-chat\u002Fsystem_requirements.md) for more details.\n\n\u003Cbr\u002F>\n\u003Cbr\u002F>\n\u003Cp>\n  \u003Ca href='https:\u002F\u002Fflathub.org\u002Fapps\u002Fio.gpt4all.gpt4all'>\n    \u003Cimg style=\"height: 2em; width: auto\" alt='Get it on Flathub' src='https:\u002F\u002Fflathub.org\u002Fapi\u002Fbadge'>\u003Cbr\u002F>\n    Flathub (community maintained)\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n## Install GPT4All Python\n\n`gpt4all` gives you access to LLMs with our Python client around [`llama.cpp`](https:\u002F\u002Fgithub.com\u002Fggerganov\u002Fllama.cpp) implementations. \n\nNomic contributes to open source software like [`llama.cpp`](https:\u002F\u002Fgithub.com\u002Fggerganov\u002Fllama.cpp) to make LLMs accessible and efficient **for all**.\n\n```bash\npip install gpt4all\n```\n\n```python\nfrom gpt4all import GPT4All\nmodel = GPT4All(\"Meta-Llama-3-8B-Instruct.Q4_0.gguf\") # downloads \u002F loads a 4.66GB LLM\nwith model.chat_session():\n    print(model.generate(\"How can I run LLMs efficiently on my laptop?\", max_tokens=1024))\n```\n\n\n## Integrations\n\n:parrot::link: [Langchain](https:\u002F\u002Fpython.langchain.com\u002Fv0.2\u002Fdocs\u002Fintegrations\u002Fproviders\u002Fgpt4all\u002F)\n:card_file_box: [Weaviate Vector Database](https:\u002F\u002Fgithub.com\u002Fweaviate\u002Fweaviate) - [module docs](https:\u002F\u002Fweaviate.io\u002Fdevelopers\u002Fweaviate\u002Fmodules\u002Fretriever-vectorizer-modules\u002Ftext2vec-gpt4all)\n:telescope: [OpenLIT (OTel-native Monitoring)](https:\u002F\u002Fgithub.com\u002Fopenlit\u002Fopenlit) - [Docs](https:\u002F\u002Fdocs.openlit.io\u002Flatest\u002Fintegrations\u002Fgpt4all)\n\n## Release History\n- **July 2nd, 2024**: V3.0.0 Release\n    - Fresh redesign of the chat application UI\n    - Improved user workflow for LocalDocs\n    - Expanded access to more model architectures\n- **October 19th, 2023**: GGUF Support Launches with Support for:\n    - Mistral 7b base model, an updated model gallery on our website, several new local code models including Rift Coder v1.5\n    - [Nomic Vulkan](https:\u002F\u002Fblog.nomic.ai\u002Fposts\u002Fgpt4all-gpu-inference-with-vulkan) support for Q4\\_0 and Q4\\_1 quantizations in GGUF.\n    - Offline build support for running old versions of the GPT4All Local LLM Chat Client.\n- **September 18th, 2023**: [Nomic Vulkan](https:\u002F\u002Fblog.nomic.ai\u002Fposts\u002Fgpt4all-gpu-inference-with-vulkan) launches supporting local LLM inference on NVIDIA and AMD GPUs.\n- **July 2023**: Stable support for LocalDocs, a feature that allows you to privately and locally chat with your data.\n- **June 28th, 2023**: [Docker-based API server] launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.\n\n[Docker-based API server]: https:\u002F\u002Fgithub.com\u002Fnomic-ai\u002Fgpt4all\u002Ftree\u002Fcef74c2be20f5b697055d5b8b506861c7b997fab\u002Fgpt4all-api\n\n## Contributing\nGPT4All welcomes contributions, involvement, and discussion from the open source community!\nPlease see CONTRIBUTING.md and follow the issues, bug reports, and PR markdown templates.\n\nCheck project discord, with project owners, or through existing issues\u002FPRs to avoid duplicate work.\nPlease make sure to tag all of the above with relevant project identifiers or your contribution could potentially get lost.\nExample tags: `backend`, `bindings`, `python-bindings`, `documentation`, etc.\n\n## Citation\n\nIf you utilize this repository, models or data in a downstream project, please consider citing it with:\n```\n@misc{gpt4all,\n  author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},\n  title = {GPT4All: Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo},\n  year = {2023},\n  publisher = {GitHub},\n  journal = {GitHub repository},\n  howpublished = {\\url{https:\u002F\u002Fgithub.com\u002Fnomic-ai\u002Fgpt4all}},\n}\n```\n","GPT4All 是一个能够在任何设备上本地运行大型语言模型（LLM）的开源项目。它支持在普通台式机和笔记本电脑上私密地运行这些模型，无需依赖API调用或GPU。项目的核心功能包括通过C++实现对DeepSeek R1 Distillations的支持，并提供了Python客户端方便用户接入。适用于需要在本地环境中使用AI聊天助手而不希望数据外传的场景，如个人隐私保护、企业内部应用等。该项目遵循MIT许可证，允许商业使用。","2026-06-17 02:35:31","top_all"]