Quick Start

Overview

What is GPU Virtual Machine?

GPU Virtual Machine (GPU VM) enables you to deploy and manage high-performance GPU servers with ease. GPU VM uses a passthrough GPU to get a dedicated GPU, applications access it through the layers of a guest OS and hypervisor. Other critical VM resources that applications use, such as RAM, storage, and networking, are also virtualized.

FPT AI Factory portal currently offers Local NVMe storage with each GPU instance.

This fixed-capacity storage is optimized for high-performance training workloads but is not suitable for long-term data retention.For persistent data storage with on-demand scaling capabilities, Block Storage – Persistent Disk is available through FPT Cloud by contacting FPT Support.

GPU VM vs GPU Container

	GPU VM	GPU Container
Environment Control	Full OS + root access(SSH, sudo) Install custom drivers, CUDA versions, and system libs Debug low-level issues (NCCL, networking, drivers)	Workload runs inside Docker Don’t care about the host OS, Pre-configured environment
Setup Speed	Slower to set up (Spin-up VMs & Software)	Starts in 1-2 minutes
Workload Type	Long-running experiments LLM training (multi-GPU) Fine-tuning with custom libs	Fast experiments Inference microservices Batch inference jobs
Networking & System Needs	Full network control Custom ports, routing, SSH Easier multi-node debugging	Depends on platform networking Extra abstraction layers
Billing model	NVMe storage is retained; full charge while stopped	NVMe** storage is cleared**; no charge while stopped (excluding persistent storage)

Quick start

Step 1: Sign up and Sign in

• Go to https://ai.fptcloud.com or https://ai.fptcloud.jp, click Sign Up, and follow the system instructions to enter your details.

• Our support team will contact you shortly to verify your information and activate your account.

• Sign in with your FPT ID username/email and password

Step 2: Add credit to account

1. Navigate to section ACCOUNT and click Billing

2. Click Add Credit button and enter an amount and payment information to complete.

Or, you have a voucher from FPT, apply your valid code in Add Voucher section to redeem credit

Step 3: Create a GPU VM

1. Select GPU Virtual machine in the Side menu.

2. Click button Create New Virtual machine and configure the VM deployment.

3. Follow the detailed guide here.

Step 3: Connect to GPU VM

1. In the GPU VM list page, click GPU VM name to access GPU VM details and the monitoring dashboard

2. Depends on your configurations in Access GPU VM section, choose one of the methods to connect: Web console with Root password or Terminal with SSH key

3. If you use the default security group, all inbound and outbound traffic is allowed for this VM.We recommend updating rules to restrict access to trusted IPs and the above exposed ports only (e.g., SSH 22, RDP 3389, HTTP/HTTPS).

4. Follow the detailed guide here.