👋 Jan

@jandotai • 13,092 subscribers

Jan is one agent for (almost) everything. Community: https://t.co/NIyIbR60qQ

Shorts

Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛

Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛

53,881 Aufrufe

Qwen3.5-35B-A3B is now in Jan 🔥 It surpasses previous Qwen3 models more than 6× its size. Get the latest Jan at Thanks to Qwen for the base model and Georgi Gerganov for llama.cpp 💛

Qwen3.5-35B-A3B is now in Jan 🔥 It surpasses previous Qwen3 models more than 6× its size. Get the latest Jan at Thanks to Qwen for the base model and Georgi Gerganov for llama.cpp 💛

34,433 Aufrufe

Someone got DeepSeek-R1-0528-Qwen3-8B running on an iPhone 16 Pro using MLX. It runs but takes ages to respond, and the phone gets hot fast. 8B models on phones aren't sci-fi anymore. via u/adrgrondin on r/LocalLLaMA

Someone got DeepSeek-R1-0528-Qwen3-8B running on an iPhone 16 Pro using MLX. It runs but takes ages to respond, and the phone gets hot fast. 8B models on phones aren't sci-fi anymore. via u/adrgrondin on r/LocalLLaMA

81,983 Aufrufe

Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at

Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at

28,193 Aufrufe

You can now use Qwen3-VL in Jan. Find the GGUF model on Hugging Face, click "Use this model" and select Jan, or copy the model link and paste it into Jan Hub. Thanks Qwen 🧡

You can now use Qwen3-VL in Jan. Find the GGUF model on Hugging Face, click "Use this model" and select Jan, or copy the model link and paste it into Jan Hub. Thanks Qwen 🧡

44,150 Aufrufe

Jan Desktop v0.7.8 is out 👋 You can now run OpenClaw agents with local models, in just a few clicks. Plus Jan CLI for your workflows, and automatic context management so you never get cut off mid-conversation. Agent support is still experimental. We're working hard on it and would love your feedback 💛 Download Jan:

Jan Desktop v0.7.8 is out 👋 You can now run OpenClaw agents with local models, in just a few clicks. Plus Jan CLI for your workflows, and automatic context management so you never get cut off mid-conversation. Agent support is still experimental. We're working hard on it and would love your feedback 💛 Download Jan:

16,680 Aufrufe

How to run AI models locally? -> Go to 🤗 Hugging Face -> Grab the GGUF model link -> Drop it into 👋 Jan Hub That's all there is to it.

How to run AI models locally? -> Go to 🤗 Hugging Face -> Grab the GGUF model link -> Drop it into 👋 Jan Hub That's all there is to it.

44,685 Aufrufe

Jan v0.6.9 is here: Chat with images now. Highlights: - Multimodal models can see images - MCP Server is now stable feature - Tool calling for gpt-oss (upstream llama.cpp upgrade) - Auto-detect tools & vision - no more manual setup Update your Jan or download the latest.

Jan v0.6.9 is here: Chat with images now. Highlights: - Multimodal models can see images - MCP Server is now stable feature - Tool calling for gpt-oss (upstream llama.cpp upgrade) - Auto-detect tools & vision - no more manual setup Update your Jan or download the latest.

22,604 Aufrufe

Hugging Face 🤝 Jan You can now use Hugging Face as a remote model provider in Jan. Go to Settings -> Model Providers -> add your Hugging Face API key. Then open a new chat and pick a model from Hugging Face. Works with any model in Hugging Face in Jan.

Hugging Face 🤝 Jan You can now use Hugging Face as a remote model provider in Jan. Go to Settings -> Model Providers -> add your Hugging Face API key. Then open a new chat and pick a model from Hugging Face. Works with any model in Hugging Face in Jan.

22,264 Aufrufe

Jan supports the new Qwen's Qwen3-4B model. Search for it in Jan Hub and download via Hugging Face to run it locally.

Jan supports the new Qwen's Qwen3-4B model. Search for it in Jan Hub and download via Hugging Face to run it locally.

14,214 Aufrufe

Jan v0.5.15: You can now tweak llama.cpp settings, and add any cloud model! Highlights 🎉 - Improved llama.cpp settings - Install & use any cloud model - Better hardware controls - New models: DeepSeek, Gemini, o3-mini, R1 distills Update your Jan or download the latest.

Jan v0.5.15: You can now tweak llama.cpp settings, and add any cloud model! Highlights 🎉 - Improved llama.cpp settings - Install & use any cloud model - Better hardware controls - New models: DeepSeek, Gemini, o3-mini, R1 distills Update your Jan or download the latest.

11,062 Aufrufe

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No Claude plan? You can still use Claude Code. Connect it to Jan and run local models on your own machine. That means no subscription and no token caps. Download Jan v0.7.7 at

No Claude plan? You can still use Claude Code. Connect it to Jan and run local models on your own machine. That means no subscription and no token caps. Download Jan v0.7.7 at

250,144 Aufrufe • vor 3 Monaten

Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro. In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally. Use cases: - Web search - Deep Research Built on the new version of Qwen's Qwen3-4B-Thinking (up to 256k context length), fine-tuned for reasoning and tool use in Jan. You can run the model in Jan, llama.cpp, or vLLM. To enable search in Jan, go to Settings → Experimental Features → On, then Settings → MCP Servers → enable a search-related MCP such as Serper. Use the model: - Jan-v1-4B: - Jan-v1-4B-GGUF: Credit to the Qwen team for Qwen3 4B Thinking & Georgi Gerganov for llama.cpp.

Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro. In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally. Use cases: - Web search - Deep Research Built on the new version of Qwen's Qwen3-4B-Thinking (up to 256k context length), fine-tuned for reasoning and tool use in Jan. You can run the model in Jan, llama.cpp, or vLLM. To enable search in Jan, go to Settings → Experimental Features → On, then Settings → MCP Servers → enable a search-related MCP such as Serper. Use the model: - Jan-v1-4B: - Jan-v1-4B-GGUF: Credit to the Qwen team for Qwen3 4B Thinking & Georgi Gerganov for llama.cpp.

689,722 Aufrufe • vor 9 Monaten

Introducing Jan-Code-4B 💻 A compact coding model tuned for practical day-to-day tasks. Generation, refactors, debugging, tests — all runnable locally in Jan. Download Jan: Model:

Introducing Jan-Code-4B 💻 A compact coding model tuned for practical day-to-day tasks. Generation, refactors, debugging, tests — all runnable locally in Jan. Download Jan: Model:

109,873 Aufrufe • vor 3 Monaten

Introducing Jan-v2-VL, a multimodal agent built for long-horizon tasks. Jan-v2-VL executes 49 steps without failure, while the base model stops at 5 and other similar-scale VLMs stop between 1 and 2. It achieves longer, stable task execution in your browser without accuracy loss. 3 variants are available: - Jan-v2-VL-low (efficiency-oriented) - Jan-v2-VL-med (balanced) - Jan-v2-VL-high (deeper reasoning and longer execution) Models: To use it, update your Jan App and download Jan-v2-VL from the Model Hub. Activate Browser MCP servers for agentic use cases. Credit to the Qwen team for Qwen3-VL-8B-Thinking base model.

Introducing Jan-v2-VL, a multimodal agent built for long-horizon tasks. Jan-v2-VL executes 49 steps without failure, while the base model stops at 5 and other similar-scale VLMs stop between 1 and 2. It achieves longer, stable task execution in your browser without accuracy loss. 3 variants are available: - Jan-v2-VL-low (efficiency-oriented) - Jan-v2-VL-med (balanced) - Jan-v2-VL-high (deeper reasoning and longer execution) Models: To use it, update your Jan App and download Jan-v2-VL from the Model Hub. Activate Browser MCP servers for agentic use cases. Credit to the Qwen team for Qwen3-VL-8B-Thinking base model.

129,906 Aufrufe • vor 6 Monaten

You can run Kimi-K2-Thinking, the most strongest agentic model, in Jan through Hugging Face. Add it to your Hugging Face Inference models to use it.

You can run Kimi-K2-Thinking, the most strongest agentic model, in Jan through Hugging Face. Add it to your Hugging Face Inference models to use it.

40,177 Aufrufe • vor 6 Monaten

Introducing a brand new way to use Jan 💛 You can now search the web, do deep research, and let Jan use your browser. Powered by Jan-v2-VL-Max, 30B model beating Gemini 2.5 Pro & DeepSeek R1 on execution benchmarks. Try it:

29,403 Aufrufe • vor 5 Monaten

Jan-v2-VL-Max-Instruct is out on 💛 Our newest 30B vision-language model, extending the Jan-v2-VL family. This is our experiment bringing interleaved reasoning to an Instruct model. It handles long tasks well and stays on track when things get complicated. Good for research, multi-step problems, anything that needs patience. Try it now at

Jan-v2-VL-Max-Instruct is out on 💛 Our newest 30B vision-language model, extending the Jan-v2-VL family. This is our experiment bringing interleaved reasoning to an Instruct model. It handles long tasks well and stays on track when things get complicated. Good for research, multi-step problems, anything that needs patience. Try it now at

23,063 Aufrufe • vor 5 Monaten

Want to reduce your Claude Code bill? Claude Code uses smaller models like Haiku for simple tasks. Instead of sending every small request to a paid API, run those tasks locally with Jan and keep heavier work in the cloud. One setup. Lower API usage. More control. Get the latest version at

Want to reduce your Claude Code bill? Claude Code uses smaller models like Haiku for simple tasks. Instead of sending every small request to a paid API, run those tasks locally with Jan and keep heavier work in the cloud. One setup. Lower API usage. More control. Get the latest version at

13,085 Aufrufe • vor 3 Monaten

Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.

Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.

17,759 Aufrufe • vor 8 Monaten

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