Install OpenMindAI on Linux.
OpenMindAI provides a Linux shell bootstrap and exercises the Linux/Tauri dependency path in CI. Real-world distributions, desktop environments and GPU stacks vary, so the Linux path is designed to be explicit and diagnosable.
openmindai-setup.sh
Confirm the device requirements.
Local AI performance depends on memory, compute, storage, model size and backend support. These requirements are based on the current project documentation.
Download and verify the release.
Use the official OpenMindAI release package rather than a third-party mirror. Published checksums should be used when available.
OpenMindAI-Setup.bat: sha256:4dcb47b4664193b1488136c55f8636a91e3623146a13967f527a85752e2ca443
OpenMindAI-Setup.command: sha256:2c547c84b62d759c6cae40c07f65bd4136c77ce3e5be30d35d35c5c74f6da7b8
openmindai-setup.sh: sha256:a1ad46dc91425ce0f165abcd0cddbe90348fcc510d60cfd8a4d778b9c07027f3
openmindai.marker: sha256:d7966cf73d439dcc7af168dd9f213ba685f0a0880e6802398ac38ad4497d038b
OpenMindAI_3.0.0_x64-setup.exe: sha256:a83f0cd1152f08801fba4332e7adf1d18aef12b7950a007d4cdab8ffa482b317Make the shell bootstrap executable.
Download the official shell bootstrap, grant execute permission, then launch it from the terminal. The exact command saved with the current release is shown below when available.
chmod +x openmindai-setup.sh
./openmindai-setup.shChoose storage, detect hardware and prepare the model.
The first-run flow is intentionally local-first and separates the desktop application from the AI data root.
Know what works offline and what still needs a network.
Designed to work offline
Local AI inference, conversation history, local settings, installed model/runtime management, project data already on the machine, diagnostics and local backup workflows.
Requires network access
Initial source/bootstrap downloads, runtime downloads, model downloads, release/update checks and any explicitly connected remote service.
Important Linux guidance.
The Linux bootstrap covers common package-manager families, while actual desktop and GPU environments can still differ significantly.
Linux should be treated as an actively validated platform rather than assumed identical to Windows.
If acceleration is unavailable, use a compatible fallback backend where supported and expect lower performance.