# Earnings & Rewards

Providers earn $OGPU by completing tasks on the OpenGPU Network.

## How You Earn

### Task Payments

Each completed task pays the provider in $OGPU:

* Payment amount set by the client
* Released automatically on successful completion
* Held in escrow during execution

### Competition Models

**First Response**

* Race to complete first
* Winner gets full task payment
* Speed matters

**Manual Confirmation**

* Attempt with suggested payment
* Client chooses best response
* Can win by offering lower price

## Factors Affecting Earnings

| Factor                 | Impact                                      |
| ---------------------- | ------------------------------------------- |
| **Hardware**           | Better GPUs = faster execution = more tasks |
| **Availability**       | More uptime = more opportunities            |
| **Sources registered** | More sources = more task types              |
| **Reputation**         | Higher success rate = better visibility     |
| **Location**           | Network latency affects response times      |

## Costs to Consider

* **Staking**: $OGPU locked as collateral
* **Hardware**: Electricity, wear, cooling
* **Network**: Bandwidth usage
* **Gas fees**: Transaction costs on OpenGPU Blockchain (negligible)

## Tracking Earnings

### Provider Suite

* Real-time earnings dashboard
* Task history and payments
* Performance metrics

### Management dApp

* Detailed analytics
* Historical data
* Multi-provider overview

Visit [management.opengpu.network](https://management.opengpu.network)

## Withdrawing Earnings

Earnings accumulate in your master wallet's Vault. From there you can:

* Withdraw to your wallet
* Use for staking
* Transfer to exchanges

## Maximizing Earnings

1. **Register for popular Sources**: More tasks available
2. **Maintain high uptime**: Don't miss opportunities
3. **Use AI agents**: Automate and optimize attempting strategies
4. **Monitor performance**: Identify and fix issues quickly
5. **Upgrade hardware**: Faster execution wins more First Response tasks

> See [AI Agents](/opengpu-network/introduction/ai-agents.md) for automating strategies.


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# 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:

```
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```

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.