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Jan

Open-source offline ChatGPT alternative

Open-source desktop app that runs LLMs fully offline as a private ChatGPT alternative, with an OpenAI-compatible local API and optional cloud models.

Maker
Menlo Research
Founded
2023
Pricing
Free tier
Last checked
October 2026

Verdict

Open-source desktop app that runs LLMs fully offline as a private ChatGPT alternative, with an OpenAI-compatible local API and optional cloud models.

Score breakdown

vs LM Studio, the category leader
CriterionWeightScoreΔ leader
Capability30%6−1
Ease of use20%7−1
Value for money20%8+1
Reliability20%70
Support & docs10%70
How we score →
Best for

Privacy-minded users who want a clean, open-source desktop ChatGPT alternative that runs models locally.

Key features

  • Runs open-source LLMs fully offline after the initial model download
  • Built-in model hub for downloading and managing GGUF models
  • OpenAI-compatible local API server (default port 1337)
  • Optional connections to OpenAI, Anthropic, Gemini and other OpenAI-compatible endpoints
  • Persistent, locally stored multi-thread chat history
  • Extension/plugin system for community add-ons
  • GPU acceleration (CUDA, ROCm, Apple Metal) plus CPU-only inference
  • Cross-platform desktop app built with Tauri (macOS, Windows, Linux)

Strengths

  • +Completely free and open source (Apache-2.0) with no subscriptions or token limits
  • +True offline operation — inference runs locally with data kept on-device
  • +Built-in OpenAI-compatible local API server makes Jan a backend for other tools
  • +Unifies local and cloud models (OpenAI, Claude, Gemini and others) in one interface

Weaknesses

  • −Model quality and speed are bound by your own hardware
  • −Desktop only — no mobile app
  • −UI is less polished than some commercial alternatives, and a few features remain 'coming soon'
  • −Past security issues were reported (and addressed); large model downloads require patience

Overview

Overview

Jan is an open-source (Apache-2.0) desktop application, first released in 2023 and maintained by Menlo Research, that positions itself as a private, offline alternative to ChatGPT. It downloads and runs open-source models locally through a built-in model hub, stores chat history on-device, and can also connect out to cloud providers like OpenAI, Anthropic and Google when you want them — all from one interface. With 43k+ GitHub stars and millions of downloads, it has a sizable community.

A defining feature is its built-in OpenAI-compatible API server (on port 1337), which lets other tools and IDEs use Jan as a local LLM backend. Built with Tauri, it runs across macOS, Windows and Linux and supports GPU acceleration as well as CPU-only inference. It is less polished than some commercial GUIs and a handful of advanced features are still in progress, but the privacy story and openness are strong.

Key Benefits

  • Open and free: Apache-2.0 with no usage caps — you own the stack.
  • Offline-first privacy: Conversations and inference stay on your device by default.
  • Local API backend: The OpenAI-compatible server turns Jan into infrastructure other apps can call.
  • One interface, many models: Switch between local and major cloud models without leaving the app.

Use Cases

  1. Private daily assistant — A ChatGPT-style experience that runs without sending data to the cloud.
  2. Local backend for tools — Use Jan’s server as a drop-in OpenAI endpoint for IDEs and scripts.
  3. Hybrid local/cloud workflows — Default to local models and reach for a frontier API only when needed.
  4. Learning local LLMs — A friendly GUI for downloading and comparing open models.

Pricing

Checked October 2026 · USD
Free (Open Source)$0
  • Full app under Apache-2.0
  • Unlimited local inference and model downloads
  • Local API server and cloud-model connections (bring your own keys)

Other local llm tools agents

AgentOverallFromBest for
LM Studio7.2FreePeople who want the easiest, most polished way to run local LLMs on a desktop — especially on Apple Silicon.
Ollama7.2FreeDevelopers and privacy-conscious users who want the fastest path to running open-weight LLMs locally or as an OpenAI-compatible drop-in.
llama.cpp7.1FreeDevelopers and power users who want maximum control and performance running open-weight models directly on their own hardware.
Msty7.1FreeUsers who want the most polished, no-setup desktop app for running local LLMs offline alongside cloud models.
Reviewed October 2026 · AI-assisted research, scores verified by an editorVisit Jan