# Renting a GPU

The Nebula AI platform provides a **decentralized, peer-to-peer GPU rental system**, allowing users to lease high-performance compute power for AI training, deep learning, rendering, and more. Renting a GPU is a streamlined process, ensuring security, flexibility, and transparent pricing. This section will guide you through the complete process, from **connecting your wallet** to **deploying workloads on a rented GPU**.

***

### **Connecting Your Wallet & Funding Your Account**

To access the Nebula AI marketplace, you must connect a **Web3-compatible wallet**.

1. Click **"Connect Wallet"** on the platform.
2. Select your preferred wallet and approve the connection.
3. Ensure your wallet is funded with **$NAI** or **ETH**.

Once connected, your wallet serves as your **Nebula AI account.**

***

### **Browsing the GPU Marketplace**

After connecting your wallet, you can browse the **available GPUs** using the marketplace interface. Each listing provides detailed specifications, ensuring you select the best GPU for your workload.

The marketplace allows you to filter GPUs by:

* **Model & Performance**
* **VRAM Size**
* **Compute Power**
* **Availability & Rental Type** (Spot vs. On-Demand)
* **Pricing & Rental Duration**
* **Location**

Clicking on a listing provides more **detailed specifications**, including performance benchmarks, uptime history, and past rental reviews.

***

### **Selecting Rental Type: Spot vs. On-Demand**

Nebula AI offers two types of GPU rentals:

#### **On-Demand Rentals (Guaranteed Access)**

* Provides **exclusive access** to a GPU for the entire rental period.
* Ideal for **long-running AI training** or **continuous workloads** that cannot tolerate interruptions.
* **Higher pricing** due to guaranteed uptime.

#### **Spot Rentals (Dynamic Pricing, Interruptible)**

* Available at **a lower cost**, but another renter may outbid you and take over the rental.
* Suitable for **batch processing tasks** and **non-urgent workloads**.
* **Great for cost savings**, but not recommended for long-term, mission-critical workloads.

You can set **maximum bid limits** for **Spot Rentals**, ensuring you only compete within your budget.

***

### **Confirming & Deploying Your Rental**

Once you’ve selected a GPU and rental type, you will proceed to payment.

1. Click **"Rent Now"** and approve the **smart contract transaction** from your Web3 wallet.
2. Once the transaction is confirmed, your rental session will start.
3. You will receive **connection details** based on the selected **access method**:
   * **SSH Credentials** (For direct Linux terminal access)
   * **Jupyter Notebook** (For ML/AI workflows)
   * **API Endpoints** (For automated workload deployment)

Your rental session will be **immediately available**, and you can start executing your workloads on the rented GPU.

***

### **Managing Your Rental Session**

Once your rental is active, you can monitor its performance from the **Rental Dashboard**. The dashboard provides:

* **Live GPU usage metrics** (VRAM, Compute Load, Power Consumption).
* **Session Timer** (Time remaining for rental).
* **Extend Rental Option** (If additional time is needed).
* **End Rental Button** (To manually stop usage before the session expires).

Rentals **automatically expire** when the time limit is reached, and all **session data is wiped**. **Make sure to back up your work before the rental ends.**

***

### **Ending Rental & Auto-Expiration**

When your rental period **expires**, the GPU is immediately released back to the marketplace. If you need more time, **you must extend the rental before expiration**.

💡 **Important Notes:**

* **No refunds** are provided for unused rental time.
* **All storage is cleared** upon expiration, so ensure you save your work externally.
* If you end your session early, the remaining time **cannot be transferred**.

For users requiring **persistent storage** across rental sessions, Nebula AI will introduce **cloud-linked storage options** in future updates.


---

# Agent Instructions: 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:

```
GET https://docs.nebulanetwork.ai/gpu-marketplace/overview/detailed-rental-guide/renting-a-gpu.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.