> For the complete documentation index, see [llms.txt](https://paragon-2.gitbook.io/paragon/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paragon-2.gitbook.io/paragon/paragon-gpu-network.md).
# Paragon GPU Network
In contrast to other networks and protocols where users mainly utilize GPU power for mining to earn rewards, Paragon Network offers a different approach. Our system reduces resource wastage by smartly managing traffic and resources, ensuring efficient use of GPU power.
On the Paragon network, users contribute their GPU resources and are rewarded accordingly.
{% hint style="info" %}
Simply put: Users who contribute GPU power receive rewards, while those using GPU power from the network pay charges.
{% endhint %}
#### Unique Selling Points (USP)?
* Minimizing GPU power wastage.
* Guaranteed uptime: Applications requiring substantial GPU power benefit from uninterrupted access to resources on the Paragon Network.
* Scalability: Our network of GPU clusters adapts to varying needs, ensuring resources are available regardless of scale.
* Enhanced security: Our GPU clusters are designed with layers of security measures to safeguard processing.
#### Use Cases?
* Bio Simulations: Complex simulations of viruses, bacteria, or other microorganisms' RNA structures can efficiently run on the Paragon Network's distributed GPU power.
* Graphic Media Rendering: Rendering tasks for games, videos, and other content are efficiently handled using our distributed GPU network.
* Language Model Training: Users can effectively train their own Language Models (LLMs) by leveraging the extensive GPU power available on the Paragon Network.
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