# FAQ

## General <a href="#contentify_0" id="contentify_0"></a>

### **1. What is GPU Virtual Machine?**

GPU Virtual Machine or **GPU VM** is an isolated system with its own dedicated **GPU, CPU, memory, network interface, and storage**, created from a **GPU Cluster** of hardware resources.

It provides a wide range of **pre-configured virtual machines** designed to align with your workload requirements, offering flexible options from **1 to 8 GPUs per VM**.

## Features <a href="#contentify_1" id="contentify_1"></a>

### **2. Can I resize a GPU instance (CPU, RAM, or Disk)?**

* **With Block Storage – Ephemeral Disk (NVMe):**\
  The GPU VM provides **pre-configured flavors** for GPU, CPU, RAM, and Disk.\
  You **cannot customize** them. Please choose an appropriate configuration or contact **FPT Cloud Support** for assistance.
* **With Block Storage – Persistent Disk:**\
  GPU, CPU, and RAM are **fixed configurations**.\
  You can **resize storage** according to your needs, but **not below 100 GB per instance**.

### **3. How can I allocate a public IP to my GPU instance?**

* **With Block Storage – Ephemeral Disk (NVMe):**\
  You can only allocate a **Floating IP** after the GPU instance is successfully created. Notice that you have to configure the IP port (port forwarding) complete the IP configuration. Please see the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-manage-floating-ips)
* **With Block Storage – Persistent Disk:**\
  You can allocate a **Floating IP** while creating a new instance or after the instance has been successfully created.

### **4. Which functions are not supported for GPU Virtual Machines with Ephemeral Disk (NVMe)?**

The following functions are **not supported** for GPU Virtual Machines using **Ephemeral Disk (NVMe)** with **NVIDIA Hopper (H100, H200)**:

* Resize instance (add/remove GPUs, resize CPU, RAM, or Disk)
* Snapshot
* Create a template from GPU instance
* Only **backup instance with Veeam** is supported.

### **5. What storage options are available for GPU Virtual Machines?**

There are **two types of Block Storage**:

1. **Ephemeral Disk (NVMe):**
   * Fixed capacity per GPU instance package (non-expandable)
   * Optimized for **training workloads**, not long-term storage
   * Does **not support automated backup or restore**
2. **Persistent Disk:**
   * Scalable storage capacity on demand
   * Optimized for **long-term retention**
   * Can set up **automated backup and restore**
   * Separate charges for storage usage (excluding GPU instance cost)

Note: File Storage (High-performance Tier) service is only supported in the Vietnam region now.

### **6. What regions are GPU Virtual Machines available?**

GPU Virtual Machines with **NVIDIA Hopper (H100, H200)** are available in the following regions:

* **Hanoi 2, Vietnam**
* **Tokyo, Japan**

## Billing <a href="#contentify_2" id="contentify_2"></a>

### **7. How can I be charged for GPU Virtual Machines?**

There are two billing models available:

* **Reservation:**\
  Fixed price with limited resources based on demand, billed upfront (partial or full) or afterward. The billing period can be **3–9 months** or **1–5 years**.
* **Pay-as-you-go (PAYG):**\
  Allows you to use resources without limits and pay afterward. Billing increments are typically by the **hour**.

### **8. Does FPT charge GPU Virtual Machines in the Stopped state?**

* **With Block Storage – Ephemeral Disk (NVMe):**\
  Yes. Instances in a **stopped** state continue to reserve the server for your use and therefore **incur charges** until you release this server.\
  If you wish to no longer accumulate charges for a server, please **DELETE INSTANCE** in the FPT Cloud portal for Customers.
* **With Block Storage – Persistent Disk:**\
  No. GPU, CPU, and RAM of stopped instances are **not charged**.\
  However, **the storage** still charged until you completely delete it.\
  \
  Notice: **You must be on the Pay-As-You-Go (PAYG) billing plan to detach a GPU.**

  Once detached, you won't be charged for GPU usage while your instance is powered off. However, when you power it back on, GPU availability is not guaranteed, due to resources may be fully consumed by other customers.

You are also billed for other **services and resources** that are attached to any GPU instance.


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