Guide / Get started

Get started

Two paths into the network. Follow Use compute to run AI workloads on rented GPUs, or Provide GPU to run the Agent on your machine and earn $PLOS. You can do both with one wallet.

Use compute

Run an AI workload on the network and download the output.

~ 1 min
1

Connect your wallet

Open the console and connect Phantom. Your Solana wallet is your identity, your balance, and how you sign deployments — no email or signup.

Don't have Phantom? Install it from phantom.app, then refresh the console.
2

Add $PLOS to your balance

Compute is paid in $PLOS, metered per second. Top up from Billing → Add funds, or enable auto-reload to refill when your balance runs low. You only ever pay for completed work.

Indicative cost: an RTX 4090 is ~0.34 PLOS/GPU-hr, so a 20-minute, 2-GPU render runs ≈ 0.23 PLOS.

3

Deploy a job

Pick a Marketplace template (or bring your own Docker image), choose a GPU and region, set a budget, and deploy. The Core System decomposes the job into work units and routes them to matching nodes automatically.

deploy
# in the console
Marketplace → choose "ComfyUI · SDXL"Deploy
   ↳ GPU: RTX 4090 ×2 · region: us-east · budget: 40 PLOS
   ↳ input: ipfs://bafy…/refs.zip
parallelos deploy \
  --template comfyui-sdxl \
  --gpu "RTX 4090" --count 2 --region us-east \
  --budget 40 --input ipfs://bafy…/refs.zip
job = client.deployments.create(
    image="docker.io/parallelos/comfyui:2.4",
    gpu="RTX 4090", count=2, region="us-east",
    inputs="ipfs://bafy…/refs.zip", max_budget=40,
)
4

Watch it run

Follow the live log stream as the image is pulled, inputs are mounted and work units execute across nodes. Progress and per-unit status update in real time.

00:00:06 OK  lease opened on node-870e · us-east
00:06:37 INFO unit 6/64 ok · gpu 79%
00:50:37 INFO processing units 37–45 / 64
01:12:00 OK  all units complete · merging outputs
5

Collect your results

On completion the outputs are assembled and uploaded as downloadable artifacts. Grab them from the deployment's Results tab, or pull them with the CLI. Fees settle automatically — failed units are refunded.

pull artifacts
parallelos pull dep_7a3f9c -o ./out
# → renders_batch.zip (248 MB), grid_preview.png, run.log

That's it — you've run a job on decentralized GPUs. Explore more templates in the Marketplace or automate with the API & SDK.

Provide GPU

Turn idle hardware into $PLOS by running the Agent.

~ 5 min
1

Check your hardware

Any modern NVIDIA GPU with 8 GB+ VRAM can contribute. More VRAM, compute and stable bandwidth mean larger units routed your way — and higher earnings.

ComponentMinimumRecommended
GPUNVIDIA · 8 GB VRAM · CUDA 11+RTX 4090 / A100 / H100
RuntimeDocker + NVIDIA Container Toolkitdriver ≥ 535
Network50 Mbps up/downwired, low jitter
2

Install the Agent

Run one command on the machine you want to contribute. The Agent connects outbound only — you never expose any ports.

install
curl -fsSL https://get.parallelos.network | sh
# PowerShell (admin)
irm https://get.parallelos.network/win | iex
docker pull parallelos/agent:latest
3

Pair your device

Open Connect Device in the console to get a one-time pairing token, then start the Agent with it. The token links this machine to your wallet.

pair & start
parallelos agent start --token plos_xxxxxxxx_xxxxxxxx
4

Verify it's online

The Agent runs a one-time benchmark. Your device appears in Devices as pending, then online once verified, and hired while running a job.

agent benchmarking GPU… RTX 4090 · 24GB
agent connected · device gpu-node-a661 online
agent awaiting work units…
5

Earn & claim $PLOS

Rewards accrue per device from completed work, performance and uptime. Watch live telemetry on the device page, and claim your balance to your wallet anytime from Earnings. Consistent uptime raises your reputation and scheduling priority.

Keep the GPU dedicated while online for the best reputation. You can pause or bring a device offline anytime from its device page.