cherry-studio vs jan
Two of the top projects in Desktop AI apps, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
cherry-studio
Cross-platform desktop chat client for many cloud and local LLM providers
jan
Desktop app that runs local models or cloud APIs, with a local server
Verdict
cherry-studio ranks higher, 75 to 64. Of the 5 score parts we measure for both, cherry-studio leads on 3, jan on none and 2 are even.
- Adoptioncherry-studio leads by 19 points, 68 to 49: a wide gap.
- FreshnessEven at 100.
- Maintenancecherry-studio leads by 3 points, 87 to 84: close to even.
- Easy to runEven at 50.
- Agent-readycherry-studio leads by 85 points, 85 to 0: a wide gap.
Pick cherry-studio if you are
Individuals wanting one desktop client for many LLM providers and local models
- Supports cloud providers plus local Ollama and LM Studio in one client
- Runs the same prompt against multiple models in a single conversation
Pick jan if you are
Users who want a local ChatGPT-style desktop app with a local API
- Runs local models and cloud providers from one app
- OpenAI-compatible local server at localhost:1337 for other applications
| What we compare | cherry-studio | jan |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 68, popular | 49, known |
| Freshness | 100, active | 100, active |
| Maintenance | 87, healthy | 84, healthy |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 85, ready | 0, none |
| Facts from GitHub and the README | ||
| Stars | 52.6k | 44.9k |
| License | AGPL-3.0 (copyleft) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | TypeScript | Rust |
| Docker | No | No |
| GPU | Optional | Optional |
| arm64 or Apple Silicon | Mentioned | Mentioned |
cherry-studio
Cherry Studio is a desktop app for Windows, macOS and Linux that talks to cloud providers such as OpenAI, Gemini and Anthropic, and to local models through Ollama and LM Studio. It includes 300+ preset assistants, simultaneous multi-model chats, document handling (text, images, Office, PDF), WebDAV backup and an MCP server integration. An Enterprise Edition with admin backend and shared knowledge bases is sold separately.
Who it is for: Individuals wanting one desktop client for many LLM providers and local models
Strengths
- Supports cloud providers plus local Ollama and LM Studio in one client
- Runs the same prompt against multiple models in a single conversation
- Installs as a desktop app with no environment setup, on Windows, Mac and Linux
- 300+ preconfigured assistants plus custom assistant creation
Weaknesses
- AGPL-3.0; commercial use outside AGPL terms needs a separate license
- Admin backend, team knowledge base and access control are Enterprise-only
- Plugin system, OCR, TTS and ASR are listed as roadmap items, not shipped
- No Docker or web deployment; desktop only, so no multi-user server in Community Edition
- GPU optional
- Needs Ollama or LM Studio (optional, for local models), WebDAV (optional, for backup)
- Models: OpenAI, Gemini, Anthropic, Ollama, LM Studio
jan
Jan is a Tauri desktop app for Windows, macOS and Linux that downloads LLMs from Hugging Face and runs them through a bundled llama.cpp engine. It can also connect to cloud providers such as OpenAI, Anthropic, Mistral and Groq. It exposes an OpenAI-compatible API at localhost:1337 and supports MCP for agent tools.
Who it is for: Users who want a local ChatGPT-style desktop app with a local API
Strengths
- Runs local models and cloud providers from one app
- OpenAI-compatible local server at localhost:1337 for other applications
- MCP integration for agentic tool use
- Engine variants for CPU, Vulkan, Metal, CUDA and ROCm builds
Weaknesses
- Desktop only; no Docker image or multi-user web deployment
- README says Apache 2.0, but license detection reports NOASSERTION
- Source build needs Node, Yarn, Rust; Windows also needs LLVM, Ninja, CMake
- Linux Arm64 is a linked how-to, not a packaged download
- RAM ≥ 8 GB
- GPU optional
- Models: GGUF via llama.cpp, Hugging Face models, OpenAI, Anthropic, Mistral
- port 1337
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