---
title: "Volumes & storage — mounts, snapshots, sharing | PowerGPU Docs"
description: "Instance disks vs network volumes on PowerGPU: creating and mounting volumes, read-only sharing across instances, snapshots, and the flat $0.08/GB/mo billing."
url: https://powergpu.ai/docs/volumes
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

# Volumes & storage

Two kinds of storage, one price: the disk born with an instance, and volumes that outlive every instance. Both bill $0.08/GB/month, per second.

## Instance disk

Sized at deploy, local NVMe, fastest possible I/O. It survives stop/start and dies with destroy. Use it for scratch, caches and the OS — anything you can regenerate.

## Network volumes

Created independently, attached to instances in the same region, NVMe-backed over the fabric:

*volumes in practice*

```
powergpu volume create --name datasets --size 500 --region eu-west-1
powergpu launch --gpu a100-sxm4 --template pytorch \
  --volume datasets:/data          # read-write
powergpu launch --gpu l40s --template vllm \
  --volume models:/models:ro       # read-only, unlimited attachments
```

- **Attachment model** — one read-write attachment at a time; unlimited read-only attachments. The classic split: one trainer writes checkpoints, a serving fleet reads the model library.
- **Region-bound** — a volume lives in one region; attach from any machine there. Cross-region moves are a snapshot + restore (bandwidth billed at $0.01/GB).
- **Resize** — grow online anytime; shrink = create smaller + copy.

## Snapshots

Point-in-time copies of an instance disk or a volume:

*snapshot & restore*

```
powergpu snapshot create i-9f2c41ab --name golden-env
powergpu volume create --from-snapshot golden-env --name env2 --size 100
```

Snapshots bill as allocated GB at the same flat rate while they exist. The common pattern: snapshot a configured environment, destroy the instance, restore next week for pennies of storage.

## Cost intuition

| Thing | Per month | Per hour |
| --- | --- | --- |
| 50 GB instance disk | $4.00 | $0.0055 |
| 500 GB model library | $40.00 | $0.0548 |
| 2 TB dataset volume | $160 | $0.219 |

Storage is the cheap line — GPU time is the expensive one. Any pattern that lets you destroy GPUs sooner (volumes, snapshots) pays for itself immediately.

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---

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