prompt-optimizer 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.
prompt-optimizer
Prompt rewriting and testing tool for web, desktop, Chrome and MCP
jan
Desktop app that runs local models or cloud APIs, with a local server
Verdict
prompt-optimizer ranks higher, 74 to 68. Of the 5 score parts we measure for both, prompt-optimizer leads on 2, jan on 1 and 2 are even.
- Adoptionjan leads by 23 points, 67 to 44: a wide gap.
- FreshnessEven at 100.
- Maintenanceprompt-optimizer leads by 7 points, 90 to 83.
- Easy to runprompt-optimizer leads by 33 points, 83 to 50: a wide gap.
- Agent-readyEven at 0.
Pick prompt-optimizer if you are
Users who write and iterate on LLM prompts and want a dedicated tool
- Ships as web app, desktop app, Chrome extension and Docker image
- Built-in MCP server at /mcp for Claude Desktop and other MCP clients
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 | prompt-optimizer | jan |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 44, known | 67, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 90, healthy | 83, healthy |
| Easy to run | 83, very easy | 50, easy |
| Agent-ready | 0, none | 0, none |
| Facts from GitHub and the README | ||
| Stars | 38k | 44.9k |
| License | custom license (read the license) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | TypeScript | Rust |
| Docker | Yes | No |
| GPU | Not needed | Optional |
| arm64 or Apple Silicon | Mentioned | Mentioned |
prompt-optimizer
Prompt Optimizer rewrites system and user prompts with an LLM you configure, then lets you test, compare and save the results as versioned favorites. It runs as a browser app, desktop app, Chrome extension or Docker container, and exposes an MCP server at /mcp with optimize-user-prompt, optimize-system-prompt and iterate-prompt tools. Model calls go straight from the client to the provider, including text-to-image and image-to-image modes.
Who it is for: Users who write and iterate on LLM prompts and want a dedicated tool
Strengths
- Ships as web app, desktop app, Chrome extension and Docker image
- Built-in MCP server at /mcp for Claude Desktop and other MCP clients
- Analysis and compare evaluation, variables, multi-turn and function-calling tests
- Client-side processing; requests go directly to the configured provider
Weaknesses
- Web version may hit browser CORS limits with local endpoints such as Ollama
- VITE_* API keys are exposed in browser assets on public deployments
- Chrome Web Store version can lag behind the latest release
- Workspace/project management is still unchecked on the roadmap
- no GPU
- Docker + Compose
- Needs LLM provider API key or compatible endpoint
- Models: OpenAI, Gemini, DeepSeek, Grok, Zhipu AI
- port 8081
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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