> ## Documentation Index > Fetch the complete documentation index at: https://novita.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Overview **GPU Instance** provides cost-effective, accessible high-performance computing with easy GPU access, making it ideal for complex AI tasks. Users benefit from on-demand rental, optimizing both efficiency and cost-effectiveness. ## Features * Rich **built-in templates** help you quickly deploy GPU instances for AI tasks out of the box; * Start a GPU instance **in seconds**, helping you quickly handle traffic peaks; * Provides nodes in **multiple global regions** to deploy GPUs closer to your users for minimal latency; * Provides **free local storage** and allows you to attach network volume, also provides free network transfer; * Billing is **accurate to the second**, charging only for the actual running time of the GPU container instances; * **Affordable pricing** save costs by up to 50%. ## Terminology * **Container Image**: Docker-compatible OCI image reference, supporting both public registries and private repositories with authentication. * **Environment Variables**: Runtime configuration key-value pairs injected into containers for dynamic configuration and secrets management. * **HTTP/TCP Ports**: Network endpoints exposed by containers for communication. HTTP ports (e.g., 80, 443) for web services, TCP ports for general network protocols. * **Container Disk**: Root filesystem partition containing OS and system binaries. Mounted as read-write at container startup. * **Volume Disk**: High-performance ephemeral storage directly attached to the GPU instance. Optimized for I/O intensive workloads but non-persistent across instance restarts. * **Network Volume**: Network-attached storage service that allows users to access and manage data through a network. Data can be stored on remote servers and accessed from any device. If you have any questions, you can first check the [FAQs for GPU Instance](/guides/faq#gpu-instance).