Join the community GPU network — step by step
Synergia is a distributed GPU network that lets you share your computer's GPU power with the community. When your machine is idle, the Synergia client runs AI inference workloads (large language models) on behalf of other users, and stops the moment you need your GPU back — for gaming, video editing, or any other GPU-intensive task.
The client is a background daemon controlled from a menu-bar tray icon. It
communicates with a central manager over an encrypted WebSocket connection and
launches llama-server locally to process requests. All inference
runs entirely on your machine — no data leaves your machine except the model
output, which is forwarded back to the requester through the manager.
Synergia is designed so that participating never compromises your machine's security or your privacy:
llama-server binds exclusively to 127.0.0.1. The local dashboard also listens on 127.0.0.1 only. No port is reachable from your local network or the internet.
The client downloads AI models automatically when assigned to a role by the cluster manager. Model files are stored in the client's data directory and can be several gigabytes each. Make sure the drive where the data directory lives has enough free space before joining:
You can see which model is currently loaded and how much disk it uses on the dashboard (Open Dashboard → worker configuration panel).
Open the download page served by your cluster manager in a browser. The page automatically detects your platform and presents the matching binary.
If your platform is not auto-detected, expand Show all platforms and choose the right build:
The macOS download is a Synergia.zip archive containing a
Synergia.app bundle. Double-click the zip to extract, then drag
Synergia.app to your Applications folder (or
~/Applications). Double-clicking the app shows only the menu-bar tray
icon — no Terminal window.
On Linux, mark the downloaded binary executable before running it:
chmod +x synergia-client-linux-amd64
On Windows, simply double-click the .exe after allowing it through SmartScreen (see the next section).
xattr -d com.apple.quarantine ~/Applications/Synergia.app
Once launched, Synergia lives entirely in the system tray (menu bar on macOS, system tray on Windows and Linux). There is no main window — the tray icon is the only persistent UI element while the client is running.
The tray menu has three options:
http://127.0.0.1:9876. The dashboard shows
connection status, consent state, configuration, and logs.
llama-server
process completely. The worker goes offline and will not receive any requests
until it is started again.
The first time you open the dashboard, you will see a consent screen. You must accept before the client will connect to the cluster and begin processing requests.
Accepting consent authorises the collection and centralisation of the following data:
llama-server) and self-update when instructed by the cluster manager.You can revoke consent at any time from the dashboard. Once revoked, the worker disconnects from the cluster and stops reporting data. Your local model files are not deleted — they remain on disk until you uninstall.
Because you are generously contributing your hardware to the cluster, you stay fully in control of how it is used. Open the dashboard at any time from the tray icon to adjust your settings.
The Preferred Role dropdown in the worker configuration panel lets you tell the manager what kind of work your GPU should handle.
llama-server instances simultaneously if VRAM permits,
maximising your contribution to the cluster.
The Start on login toggle appears on the dashboard just below the consent banner. When enabled, Synergia is registered as a login item and starts automatically in the background every time you log in to your account — no need to launch it manually.
.desktop file is placed in ~/.config/autostart/.HKCU\Software\Microsoft\Windows\CurrentVersion\Run.The Allow log streaming toggle appears on the dashboard just below the Start on login setting. It is off by default. When enabled, the cluster administrator can request your client logs to be streamed live to the manager — for example to diagnose a connectivity problem or a model loading failure on your machine.
The same structured log lines you see in the built-in log viewer are forwarded in
real time. Each line contains a timestamp, a log level (DEBUG /
INFO / WARN / ERROR), and a short message.
No model weights, work-unit payloads, or personal files are included.
Uncheck Allow log streaming at any time to stop forwarding logs. The change takes effect immediately — any active stream is terminated within seconds.
The View Logs button at the bottom of the dashboard opens the built-in log viewer. It shows a live stream of all client messages and is the first place to look when diagnosing connection issues or unexpected behaviour.
The toolbar has four controls:
| Control | Description |
|---|---|
| Display | Filter which log levels are shown — all, debug, info, warn, error. |
| Runtime level | Change the minimum level the client actually emits at runtime. Switching to debug adds verbose handshake, status, and GPU probe messages. Switch back to info to reduce noise. |
| Search / regexp | Filter the visible lines by a plain string or regular expression. |
| Auto-scroll | When checked, the view automatically scrolls to the latest entry as new lines arrive. |
The Refresh button manually reloads the log buffer, and Clear wipes the on-screen view (the underlying log file is not deleted).
info each time the client restarts. It is not persisted.
To remove Synergia completely, use the Uninstall button at the bottom of the dashboard. This will:
On Windows, the Uninstall button is not available from the dashboard because deleting a running executable is not permitted by the OS. To uninstall manually:
synergia-client-windows-amd64.exe binary.%APPDATA%\Synergia).HKCU\Software\Microsoft\Windows\CurrentVersion\Run → delete the Synergia key.
The identity fingerprint shown on the dashboard is a stable cryptographic identifier derived from your hardware. If you reinstall on the same machine, the same fingerprint will be generated and your worker history in the cluster will be preserved.