> For the complete documentation index, see [llms.txt](https://shardgpu.gitbook.io/shardgpu/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://shardgpu.gitbook.io/shardgpu/shard-gpu/introducing-shardgpu.md).

# Introducing ShardGPU

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## **Introducing ShardGPU – The Future of Decentralized AI Compute**

The **demand for high-performance GPU power** has never been greater. AI companies, researchers, and developers are locked in a **bidding war** for compute resources, driving costs through the roof and limiting access to innovation. **Cloud providers** (AWS, Google Cloud) hold a **monopoly** over AI compute, forcing businesses to **pay premium prices for limited scalability**.

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### **ShardGPU changes the game.**

We are building a **decentralized GPU marketplace**, where **AI companies** can **access cost-efficient, scalable compute power**, and **GPU owners** can **monetize their idle resources** without lifting a finger.

This is **more than just a marketplace**—it’s a **fundamental shift** in how **AI, Web3, and high-performance computing** are powered.

With **AI-driven resource allocation, GPU virtualization, and federated learning**, **ShardGPU makes AI compute cheaper, faster, and truly decentralized**.

* **For AI Companies:** Tap into **a global network of GPUs**—pay only for what you use, with **no centralized middlemen**.
* **For GPU Owners:** Earn **passive income** from your unused GPU power while keeping your system **fully functional**.