> For the complete documentation index, see [llms.txt](https://docs.cerebrum.dev/cerebrum/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cerebrum.dev/cerebrum/technology-stack/reputation-system.md).

# Reputation System

**Supplier Reputation Tracking:** Cerebrum implements a reputation system that continuously monitors the performance of every GPU supplier. This will monitor such metrics as:

* Uptime and Reliability: The consistency in the availability of GPUs supplied.
* Completion Rates: The successful completion rate of tasks run on resources supplied by the supplier.

**Benefit from Positive Reputation -** A high reputation opens the way for:

* Increased Allocation: Cerebrum Cloud prioritizes the dispatching of tasks to suppliers with a reputation for reliability.
* Premium Pricing: Suppliers whose rating is constantly high can quote a premium on the resources supplied for compute.

**Diverse Supplier Network:** Cerebrum invites participation from a wide network of GPU suppliers, including:

* Individual Compute Owners: Those in possession of powerful GPUs can contribute and earn tokens by their contribution to the network. In a hope to democratize access and bring in wider participation, Cerebrum foregrounds individual contributors for certain tasks if they meet their criteria, placing them on par with institutional suppliers.
* Well-Established Suppliers: Larger data centers and organizations with big GPU farms can also plug into Cerebrum to monetize their resources and contribute to the AI development ecosystem.