Primary tested platform
Windows x64
- Windows 10 or 11, 64-bit
- Modern x64 CPU
- 16 GB RAM recommended
- SSD storage strongly recommended
- Compatible GPU can improve inference speed
Compatibility
Know what your device can run.
OpenMindAI adapts to available hardware, but local AI performance still depends on memory, compute, model size and backend support.
Platform compatibility
Choose hardware for the workload you want.
Local AI speed depends on CPU, GPU, memory, model size, quantization, context length and the selected backend.
Active validation
macOS
- Recent macOS release
- Intel or Apple Silicon bootstrap path
- 16 GB memory recommended
- Enough SSD space for models and runtime
- Distribution signing/notarization applies
Active validation
Linux x64
- Modern 64-bit Linux distribution
- Tauri/WebKitGTK desktop dependencies
- 16 GB RAM recommended
- SSD storage recommended
- Linux ARM64 is not currently supported
CPUCompatibility path when acceleration is unavailable
GPUCan improve inference when backend support exists
Memory16 GB recommended for baseline local-model use
StorageModels and runtimes can consume many gigabytes
Storage planning
Keep AI data where capacity exists.
The selected storage root can hold models, runtimes, SQLite data, cache, logs, generated files, workspaces, knowledge data and backups. A fast SSD or external SSD is the practical choice for larger libraries.
Building from source
Development has a separate toolchain.
The repository uses Node.js 24 in CI, a current stable Rust toolchain and platform-specific Tauri build dependencies. Windows source builds also require the normal Microsoft C++/MSVC tooling.
LOCAL-FIRST DESKTOP AI
Ready to put the workspace on your machine?
Start with the latest published release, then choose where your models and local data should live.