---
title: "GPU instance lifecycle — states, actions, interruptions | PowerGPU Docs"
description: "Instance state machine: pending, running, stopped, destroyed — what each action does, what bills in each state, how interruptible instances pause and requeue."
url: https://powergpu.ai/docs/instances
last_modified: 2026-09-14T11:04:20+00:00
prices_as_of: 2026-09-14
site: PowerGPU (powergpu.ai)
---

Compute 2 min read updated 2026-09-03

# Instance lifecycle

An instance is a GPU allocation + a disk + a template. This page is the complete state machine — what changes state, and what each state costs.

## States

| State | Meaning | GPU bills | Disk bills |
| --- | --- | --- | --- |
| pending | capacity reserved, image pulling / VM booting | no | yes |
| running | workload live, ports reachable | **yes** | yes |
| stopped | processes halted, disk intact, GPU released | no | yes |
| destroyed | gone — disk erased (volumes survive) | no | no |

Transitions are per-second precise: the billing row for a stop written at 14:02:37 ends at 14:02:37.

## Actions

- **Deploy** — needs ≥ $0.10 balance; price is locked to the sheet at that moment.
- **Stop** — graceful signal, then halt. Use it liberally: stopped instances cost only their disk.
- **Start** — re-acquires a GPU on the same machine class and resumes from disk. If the exact machine is busy, the start queues until capacity frees (you can destroy instead at any time).
- **Destroy** — immediate, irreversible for the instance disk. Attached volumes detach unharmed.

*CLI*

```
# the same four verbs everywhere
powergpu launch --gpu rtx-4090 --template pytorch --disk 50
powergpu stop    i-9f2c41ab
powergpu start   i-9f2c41ab
powergpu destroy i-9f2c41ab
```

## Interruptible instances

Interruptible capacity (−50%) can be *paused* when an on-demand deploy needs the slot:

1. The instance receives SIGTERM and a 30-second grace window;
2. it moves to stopped — disk intact, GPU billing over;
3. with auto-requeue on (default), it rejoins the queue and restarts when capacity frees;
4. a console event (and webhook, if configured) records both edges.

Design rule: write checkpoints to a [volume](https://powergpu.ai/docs/volumes) and make your entrypoint resume from the latest one. Then interruptions cost seconds, not work.

## Access

Every instance gets a hostname (i-xxxxxxxx.powergpu.ai) and its template's ports mapped to high ports on it. SSH is available on templates that ship it (a key you provide at deploy, or the in-console web terminal); VMs add full console access. See [networking](https://powergpu.ai/docs/networking) for the port model.

## Events & monitoring

The instance page streams state changes, GPU/RAM utilisation and the live cost counter. The same data is available from GET /v1/instances/{id} for dashboards and schedulers.

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