Installing on Ubuntu
Server Requirements
The server (or rig – these terms are nearly interchangeable in this context) must be equipped with NVIDIA GPUs, as AMD is currently not supported. The minimum required disk space is 32 GB (at least 30 GB free on the system partition is recommended); for reliability, it's recommended to use an SSD instead of a flash drive. A minimum of 8 GB of RAM is required, but 16 GB will provide greater stability. As for the CPU, the system can work with a Celeron on a 1151 socket, but for more efficient performance, consider using a CPU like the i7-6700.
Before proceeding, it is highly recommended to disable any overclocking, including the Power Limit (PL), and reset the GPUs to factory settings. Afterward, stress-test the system for stability by, for example, testing the GPUs using the kawpow algorithm and loading the CPU. Monitor temperatures and ensure everything is running stably.
If the system operates stably and temperatures are within a safe range, continue to the next step in the instructions. If temperatures are too high or errors occur, address these issues first – for example, by improving cooling or troubleshooting – and ensure stable operation before proceeding.
Recommended OS & Drivers
Operating System
Ubuntu 22.04 LTS — recommended, best GPU driver compatibility
Ubuntu 24.04 LTS — supported, but kernels 6.16+ may have issues with older driver branches (R550 and below)
The installer requires an x86_64 machine running Ubuntu 22.04 or newer (or HiveOS — see Installing Software). Ubuntu 18.04 and 20.04 are no longer supported.
NVIDIA Drivers
The installer does not install or upgrade GPU drivers — a working NVIDIA driver must be installed before you run it (nvidia-smi must work).
R580 (LTSB)
580.126.18
Up to CUDA 12.8
Most GPUs, long-term stability
R590
590.48.01
Up to CUDA 13.1
RTX 50 series, latest features
Install the recommended driver:
Or for RTX 50 series:
CUDA Toolkit (for ML/AI workloads)
Renters running ML workloads expect CUDA. Recommended versions:
CUDA 12.8
R570+
Stable, wide ecosystem support
CUDA 13.1
R590+
Latest, RTX 50 series optimized
Most Docker images include their own CUDA runtime, so hosts don't always need to install the CUDA Toolkit system-wide. However, having compatible drivers is essential.
Adding the Server
Everything is driven by a single install command that the dashboard generates for you.
1. Create the server on the website
Go to clore.ai, register or log in, open My Servers and click Add Server. Two paths are available:
Quick — the dashboard shows one ready-to-copy command that installs the hosting agent and registers the machine to your account in one step. The server appears in My Servers automatically with default settings (max rental length 300 hours, USD autopricing at $5 per server per day for on-demand and spot) which you can adjust from the dashboard afterwards.
Advanced — you name the server first, it appears in My Servers as awaiting installation, and the server page shows the install and register commands for it (including a combined one-liner with your server's token).
The same modal's Mass section covers bringing up whole fleets — see Clore Fleet (Mass onboarding).
2. Pick an installer channel
The generated commands come in three channels:
Stable
Recommended — thoroughly tested releases, updated less frequently
Beta
Newest updates and features before they reach Stable — may be less reliable
Legacy
Previous-generation installer — a fallback if Stable does not work on your machine
The commands per channel:
Stable (recommended):
Beta:
Legacy:
You can switch a running server between Stable and Beta updates later from its server page (requires an up-to-date hosting agent; not possible while the server is rented).
3. Run the install command as root
Then paste the command copied from the dashboard. If you used the Advanced path, append the token shown on the server's page to install and register in one step:
If you ran the plain install command without a token, register the machine afterwards with:
The installer checks its prerequisites up front and tells you what is missing. It needs outbound access to the Docker and NVIDIA package repositories, GitHub, GitLab, Docker Hub, and api.clore.ai — see Network Requirements.
4. Finalize
Reboot the rig, wait a moment, and refresh the My Servers page. If everything was set up correctly, the server will show as online.
How to Disable All Installed Services
If you need to disable everything previously installed:
Disable the services:
Reboot the system:
How to Re-enable Services
To re-enable the services:
Enable the services:
Reboot the system:
Removing the Previously Installed Token
To delete the token, use the command:
The file containing the token is located at:
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