--- title: GPUBank docs: quickstart, CLI, API and guides url: https://gpubank.io/docs description: Rent a GPU on GPUBank in five minutes: sign up, top up from $25, add an SSH key, launch. Guides for ComfyUI, vLLM, fine-tuning, plus CLI and API. generated: 2026-11-02T00:25Z publisher: GPUBank (GPU Compute OÜ, Tallinn, Estonia) summary_for_ai: https://gpubank.io/llms.txt full_text_for_ai: https://gpubank.io/llms-full.txt --- > Markdown version of https://gpubank.io/docs, generated from the live page. GPUBank is a GPU cloud billed by the second at one all-in price per GPU (vCPU, RAM, NVMe, a public IPv4 and traffic included), in Paris, Frankfurt, Ashburn and Singapore. Prices are in US dollars, excluding VAT. Docs # GPUBank documentation How to rent a GPU, connect to it and pay only for the seconds it runs. The quickstart is right below. CLI 1.4 API v1 Updated 2 November 2026 ## Launch your first GPU in five minutes. You need an email address, $25 in any supported coin and an SSH key. No compute is billed until your machine passes its health check. 1. 1 ### Create an account Sign up at [console.gpubank.io/register](https://console.gpubank.io/register) with an email and a password of 12 characters or more. We send a six-digit code to confirm the address. Signing in with GitHub or Google works too. 2. 2 ### Top up your balance In the console, open Billing › Top up and choose an amount from $25. Pay in Bitcoin, USDT, Ethereum, Monero or another listed coin. The balance is credited once the payment confirms on chain, usually within a few minutes, and a $100 top-up is credited as $135. 3. 3 ### Add an SSH key If you do not have one yet, create it on your computer, then paste the public key in Account › Security › SSH keys. Every machine you launch gets it. bash ``` ssh-keygen -t ed25519 -C "you@company.com" cat ~/.ssh/id_ed25519.pub ``` 4. 4 ### Launch a GPU From the console: Pods › Launch, then pick a GPU, a region, a template and a disk. Or from your terminal: bash ``` pipx install gpubank gpubank login gpubank launch --gpu h100-sxm --region eu-paris --disk mydisk --template pytorch-2.8 ``` output ``` ✓ instance inst_7c1e created ✓ allocated GPU H100 SXM in eu-paris 12.34 s ✓ attached disk mydisk (200 GB) 28.11 s ✓ health check passed, billing started 47.80 s connect: ssh root@par1-g07.gpubank.io ``` billing starts here 5. 5 ### Connect and check the GPU bash ``` ssh root@par1-g07.gpubank.io nvidia-smi ``` **What you are paying now.** The meter started at 47.8 s, when the health check passed. Run `gpubank stop inst_7c1e` and compute billing stops; the disk and the IP address are kept, and the disk costs $0.03 per GB-month until you delete it. 6. 6 ### Open a port and move your files Expose a web app on the public HTTPS address of the machine, and copy your data with the tools you already use. bash ``` gpubank port open inst_7c1e 8188 # https://par1-g07-8188.gpubank.io rsync -avP ./dataset/ root@par1-g07.gpubank.io:/workspace/dataset/ ``` Files under `/workspace` live on the persistent disk and survive every stop. Everything else sits on the local NVMe and is wiped when the machine stops. ## Guides for what people run on GPUBank. ### Run ComfyUI Start ComfyUI with your models on a persistent disk and open it in the browser. RTX 4090 or RTX 5090 6 min ### Serve a model with vLLM An OpenAI-compatible endpoint for Llama, Qwen or Mistral, with an API key in front. RTX PRO 6000 or H100 SXM 8 min ### Fine-tune with Unsloth LoRA or QLoRA on Llama 3.1 8B to 70B, with checkpoints written to your disk. A100 SXM or H100 SXM 10 min ### JupyterLab Notebooks with the GPU visible in PyTorch and JAX, reached over HTTPS. L40S or A100 SXM 4 min ### Ollama Pull a model, chat over the API and keep the weights on your disk. L40S or RTX 5090 4 min ### Bring your Docker image Launch any OCI image from a public or private registry, GPU passthrough on. Any GPU 5 min ### Expose a port Serve a web app or an API on an HTTPS address, with or without a token in front. Any GPU 3 min ### Transfer files scp, rsync, Hugging Face downloads with your token, and S3-compatible buckets. Any GPU 5 min ### Move a disk to another region Copy a persistent disk from Paris to Frankfurt or Ashburn and launch there. Any GPU 3 min ### Checkpoints on interruptible GPUs Catch the five-minute notice, save state and resume on the next card. Any GPU 7 min ## Start from a tested image. Each template pins the driver, CUDA and libraries, and is relaunched on every GPU model before we mark it verified. All 25 are re-checked at least every three days. | Template | Tag | First start | Verified | | --- | --- | --- | --- | | PyTorch 2.8 · CUDA 12.8 | pytorch:2.8-cu128 | about 2 min | 2026-11-01 | | Ubuntu 24.04 · CUDA 12.8 | ubuntu:24.04-cu128 | about 1 min | 2026-11-01 | | JupyterLab 4 | jupyter:4.3-cu128 | about 1 min | 2026-11-02 | | ComfyUI · model sync | comfyui:0.3-cu128 | about 4 min | 2026-11-02 | | vLLM 0.11 serving | vllm:0.11-cu128 | about 3 min | 2026-10-31 | | SGLang | sglang:0.4-cu128 | about 3 min | 2026-11-01 | | Ollama | ollama:0.12 | about 2 min | 2026-10-31 | | Text Generation Inference | tgi:3.3 | about 3 min | 2026-11-02 | | Axolotl fine-tuning | axolotl:0.9-cu128 | about 2 min | 2026-10-31 | | Unsloth | unsloth:2025.9-cu128 | about 2 min | 2026-11-02 | | faster-whisper API | whisper:faster-1.2 | about 1 min | 2026-11-01 | | InvokeAI | invoke:5.6 | about 3 min | 2026-10-31 | | Kohya trainer | kohya:25.1 | about 3 min | 2026-11-02 | | PyTorch on ROCm 6.4 | rocm-pytorch:2.8-rocm6.4 | about 3 min | 2026-10-31 | | Ubuntu 22.04 · CUDA 12.4 | ubuntu:22.04-cu124 | about 1 min | 2026-11-02 | | Debian 12 · CUDA 12.8 | debian:12-cu128 | about 1 min | 2026-11-01 | | CUDA 12.8 devel | cuda:12.8-devel | about 2 min | 2026-11-01 | | Ubuntu 24.04 · ROCm 6.4 | rocm:6.4-ubuntu | about 1 min | 2026-11-02 | | VS Code in the browser | code-server:4.99 | about 1 min | 2026-10-31 | | TensorFlow 2.19 | tensorflow:2.19-cu128 | about 2 min | 2026-11-02 | | SD WebUI Forge | forge:2.x-cu128 | about 3 min | 2026-10-31 | | Open WebUI + Ollama | open-webui:0.6-ollama | about 2 min | 2026-11-01 | | llama.cpp server | llamacpp:server-cu128 | about 1 min | 2026-10-31 | | TensorRT-LLM · Triton | trtllm:0.19-triton | about 6 min | 2026-10-31 | | ComfyUI · video (Wan 2.2) | comfyui-video:0.3-wan2.2 | about 5 min | 2026-11-01 | | Your Docker image | any OCI image | your build | on launch | ## Core concepts. **Pod** An interactive machine with one to eight GPUs, SSH and a public IPv4. You start, stop and resume it. **Job** A command that runs to completion on a GPU, then stops by itself. Billed for its running seconds only. **Endpoint** An OpenAI-compatible inference URL that scales its workers with traffic. In beta. **Disk** Persistent storage in one region, billed at $0.03 per GB-month. It survives every stop and can move to another region. **Scratch** The local NVMe of the machine, included in the price and wiped when the machine stops. **Region** Where the GPU and the disk physically are: eu-paris, eu-frankfurt, us-ashburn or ap-singapore. **Meter** Counts running seconds from the passed health check to the stop, and draws them from your balance. **Balance** Prepaid, in US dollars, topped up in crypto. Every running second is drawn from it, and a low-balance alert warns you first. ## The CLI, the API and Terraform do what the console does. CLI `launch`, `ls`, `ssh`, `stop`, `resume`, `rm`, `port open`, `disk mv`, `logs`. Installed with pipx, authenticated with `gpubank login`. Python SDK and Terraform `pip install gpubank`, then `gpubank.Client()` reads `GPUBANK_TOKEN`. Terraform resources: `gpubank_instance`, `gpubank_disk`, `gpubank_spend_cap`. REST API Base URL `https://api.gpubank.io/v1`, with a bearer token created in Developers › API keys. Every console action has an endpoint. From inside a machine, `http://169.254.169.254/gpubank/v1/` returns the instance id, the GPU, the region and, on interruptible machines, the pending notice. bash ``` curl https://api.gpubank.io/v1/instances \ -H "Authorization: Bearer $GPUBANK_TOKEN" \ -H "Content-Type: application/json" \ -d '{"gpu": "h100-sxm", "region": "eu-paris", "disk": "mydisk"}' ``` Webhooks Signed with HMAC-SHA256 in the `GPUBank-Signature` header, retried for 24 hours until your endpoint answers 2xx. `instance.ready` `instance.stopped` `instance.interruption_notice` `instance.failed` `disk.moved` `balance.low` `spend_cap.reached` json ``` { "type": "instance.interruption_notice", "created": "2026-10-04T09:41:12Z", "data": { "id": "inst_7c1e", "stops_at": "2026-10-04T09:46:12Z" } } ``` ## Limits and quotas. | Limit | Default | Can it be raised? | | --- | --- | --- | | GPUs per machine | 1, 2, 4 or 8 (up to 4 on the RTX 5090 and RTX 4090) | Fixed by the hardware | | GPUs running at once, per account | 16 | Yes, on request | | API requests | 600 per minute per key | Yes, on request | | Size of one persistent disk | 10 TB | Yes, on request | | Disks per region | 20 | Yes, on request | | Webhook endpoints | 10 per account | No | | SSH keys | 50 per account | No | To raise a limit, open a ticket from the console with the limit, the new value and what it is for. Most requests are handled the same day. ## When something does not work. The launch says queue. That GPU is sold out in the region. Queue the launch, set an availability alert, or move your disk to a region with stock. SSH asks for a password. The key on your computer is not the one in Account › Security. Check with ssh -v which key is offered. nvidia-smi shows no GPU inside your own image. Your image needs the NVIDIA container runtime libraries; start from one of our templates or set NVIDIA_VISIBLE_DEVICES=all. My files are gone after a stop. They were outside /workspace, on the local NVMe, which is wiped at stop. Keep anything you need under /workspace. A top-up has not arrived. It is credited after the network confirmations shown on the payment page. If it is still pending an hour later, open a ticket with the 8-character top-up reference. [Status Live state of every region and the incident history, in the console.](https://console.gpubank.io/status) [Changelog What changed in the console, the CLI and the API, dated, newest first.](https://gpubank.io/#public) [Something wrong in these docs? Open a ticket from the console with the page and what you expected.](https://console.gpubank.io/support/new)