> For the complete documentation index, see [llms.txt](https://ai-docs.fptcloud.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai-docs.fptcloud.com/fpt-gpu-cloud/gpu-container.md).

# GPU Container

### What is GPU Container? <a href="#contentify_0" id="contentify_0"></a>

GPU Container is a managed compute platform that lets you run containers directly on top of FPT’s AI Factory infrastructure. With just a few clicks, you can deploy and manage AI workloads effortlessly—whether by using your own container images or leveraging the built-in images provided by FPT.

### How does it work? <a href="#contentify_1" id="contentify_1"></a>

A GPU container runs applications in an isolated environment with direct access to GPU resources. It uses tools like the NVIDIA Container Toolkit to leverage GPU acceleration for tasks like AI, ML, or data processing—without complex setup.

### Why GPU container? <a href="#contentify_2" id="contentify_2"></a>

1. **Containerized AI Deployment:** Runs AI workloads in containers.
2. **High-Performance GPU Compute:** Access to NVIDIA GPUs for AI/ML workloads.
3. **Quick Deployment**: Spin up a container with a powerful GPU in 1 click using our built-in templates.
4. **Persistent Storage**: This storage is persistent and will be available even if the container is stopped.


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