---
title: "GPU Cloud CLI — Launch & Manage GPUs from Your Shell | PowerGPU"
description: "The powergpu CLI: pip install powergpu, then search offers, launch templates, stream logs, stop and destroy — every console action, scriptable."
url: https://powergpu.ai/cli
last_modified: 2026-09-14T11:04:20+00:00
prices_as_of: 2026-09-14
site: PowerGPU (powergpu.ai)
---

Developers · CLI

# The powergpu CLI: the console, without the browser

One package installs the CLI and the Python SDK. Every command maps 1:1 onto the [REST API](https://powergpu.ai/api), so anything you can click, you can script — and anything you script behaves exactly like the console did.

## Install & authenticate

*setup, once*

```
pip install powergpu
export POWERGPU_API_KEY=pg_live_…   # console → API keys
powergpu whoami
# account ok · balance $41.22 · 2 instances running
```

The key can also live in ~/.config/powergpu/config.toml — the CLI reads the environment first, then the file. Create keys in the [console](https://cloud.powergpu.ai/app/keys) ([key docs](https://powergpu.ai/docs/api-keys)).

## Find capacity

*search*

```
# the price sheet, in your terminal
powergpu gpus --sort price

# machines matching a shape
powergpu offers --gpu rtx-4090 --num 2 --region eu-west-1
# ID          GPU        ×  REGION      vCPU  RAM    DISK   $/HR
# m-8b02c1f3  RTX 4090   2  eu-west-1   16    64GB   1TB    0.654
```

## Launch & manage

*lifecycle*

```
powergpu launch --gpu rtx-4090 --template comfyui --disk 60
# ✓ instance i-b81f02aa running (28.4s)
# ✓ https://i-b81f02aa.powergpu.ai:8188  (comfyui)

powergpu list                     # your fleet, states, burn/hr
powergpu logs i-b81f02aa -f       # stream container logs
powergpu stop i-b81f02aa          # GPU billing ends this second
powergpu start i-b81f02aa
powergpu destroy i-b81f02aa --yes
```

## Volumes & snapshots

```
powergpu volume create --name models --size 500 --region eu-west-1
powergpu launch --gpu l40s --template vllm --volume models:/models:ro
powergpu snapshot create i-b81f02aa --name golden
```

## Scripting patterns

Every command takes --json for machine-readable output, and exit codes follow convention (0 ok, 1 API error, 2 usage):

*ephemeral GPU jobs*

```
# deploy, wait, run, destroy — a disposable GPU in a Makefile
ID=$(powergpu launch --gpu rtx-4090 --template pytorch --json | jq -r .id)
powergpu wait "" --state running
powergpu exec "" -- python train.py
powergpu destroy "" --yes
```

## Shell completion

```
powergpu completion bash >> ~/.bashrc     # zsh & fish too
```

Building in Python instead? The [SDK page](https://powergpu.ai/sdk) shows the same flows as typed calls.

Stuck?

Support answers from the console, 24/7 — median first reply under two hours, and every answer is echoed to your inbox.

[Open a ticket](https://cloud.powergpu.ai/app/support)

Build against it

- [REST API](https://powergpu.ai/api)
- [CLI](https://powergpu.ai/cli)
- [Python SDK](https://powergpu.ai/sdk)
- [Guides](https://powergpu.ai/guides)

---

*About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API.

Source: https://powergpu.ai/cli · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt