> For the complete documentation index, see [llms.txt](https://useterra.gitbook.io/terra/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://useterra.gitbook.io/terra/terra-ecosystem/terra-gpu-and-vm-lending.md). # Terra GPU & VM Lending #### **Terra’s GPU and VM Lending Program (RWA Connection)** Terra’s **GPU and VM Lending Program** transforms idle hardware, such as GPUs, VMs, and servers, into income-generating assets. Participants contribute their underutilized computing resources to Terra’s decentralized network, where they are used for tasks like cryptocurrency mining, AI model training, and cloud applications. In return, hardware owners earn a share of the revenue generated. This program integrates with Terra’s **Real-World Asset (RWA)** infrastructure, where each hardware contribution is tokenized on the blockchain. This ensures transparent revenue sharing and creates a secure, decentralized ecosystem for contributors and renters alike. *** #### **Key Benefits of GPU and VM Lending** **1. Monetize Idle Resources** Turn unused hardware into consistent revenue streams: * **Passive Income**: Earn real-time rewards for computational tasks performed by your hardware. * **Maximized Utility**: Use spare GPUs, VMs, or servers to generate income instead of letting them depreciate. * **Flexible Contribution**: Participate at any scale, from single devices to entire server farms. *** **2. Enhance Network Efficiency** Contributed hardware strengthens Terra’s resource pool, enabling: * **Dynamic Scaling**: Efficiently meet user demand for GPUs and VMs. * **Cost Reduction**: A larger hardware pool drives down rental prices for users. * **Optimized Utilization**: Terra’s algorithms minimize downtime and ensure maximum resource efficiency. *** **3. Strengthen Decentralization** A diverse hardware base improves Terra’s decentralization: * **Increased Resilience**: Minimize outages and single points of failure. * **Global Coverage**: Hardware from multiple regions reduces latency and enhances network performance. * **Enhanced Security**: A distributed network is harder to disrupt, ensuring stability. *** **4. Accessible to All** Terra’s program is user-friendly and inclusive: * **Low Barriers**: Contribute any scale of hardware, from single GPUs to data centers. * **Easy Onboarding**: Intuitive setup ensures participation without technical expertise. * **Customizable Options**: Retain control over your hardware’s availability and usage. *** #### **Sustainability and Transparency** * **Environmental Impact**: Extend the lifespan of existing hardware and reduce e-waste. * **Blockchain-Based Revenue**: Tokenization ensures fair earnings and transparent distribution. *** #### **Why Participate?** The GPU and VM Lending Program offers a seamless way to monetize underused hardware while supporting Terra’s decentralized ecosystem. Whether you’re an individual or an enterprise, you can turn idle resources into profitable assets and contribute to the future of decentralized computing. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://useterra.gitbook.io/terra/terra-ecosystem/terra-gpu-and-vm-lending.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.