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.
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.
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.
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.
# 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, )
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.
00:06:37 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
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.
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.
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.
| Component | Minimum | Recommended |
|---|---|---|
| GPU | NVIDIA · 8 GB VRAM · CUDA 11+ | RTX 4090 / A100 / H100 |
| Runtime | Docker + NVIDIA Container Toolkit | driver ≥ 535 |
| Network | 50 Mbps up/down | wired, low jitter |
Install the Agent
Run one command on the machine you want to contribute. The Agent connects outbound only — you never expose any ports.
curl -fsSL https://get.parallelos.network | sh# PowerShell (admin) irm https://get.parallelos.network/win | iex
docker pull parallelos/agent:latestPair 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.
parallelos agent start --token plos_xxxxxxxx_xxxxxxxx
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 connected · device gpu-node-a661 online
agent awaiting work units…
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.