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🖥 Decentralized GPU cloud

Rent a GPU by the second. Or earn from your own.

Compute is a two-sided GPU network — deploy VMs, containers and bare metal from a 47-GPU catalog, or run the open-source worker and earn credits from hardware you already own.

RACK-01 LIVE 4090 A100 H100 H200 Rent deploy a GPU by the second $0.39/hr Earn host your idle GPU 120 cr/hr
A two-sided network

Workers supply the power. Renters use it.

Compute connects two sides with no middleman. Hardware owners run an open-source worker and earn credits whenever their GPUs take a job. Renters spend credits to deploy instances on demand. Every site built on the Platform is a real job — so demand is guaranteed, not speculative.

WorkersGPU owners run the open worker
🖥
Compute networkmatches jobs to hardware
💻
Rentersdeploy GPU instances on demand
Rent — the GPU cloud

Deploy a GPU instance in seconds

VMs, containers, Kubernetes and bare metal — from a 47-GPU catalog, billed per second, no contracts.

💻Virtual Machines 📦Containers Kubernetes 🧮Bare metal Per-second billing
Pick the GPU for the job

One catalog, entry cards to H200.

The catalog spans consumer cards for light inference all the way to multi-GPU datacenter nodes. Tell Compute the workload and it filters to the GPUs that fit; pick one and it deploys with your template attached.

  • Up to 4× consumer GPUs, up to 8× datacenter GPUs per node
  • Every card benched — real tokens/sec, not spec-sheet numbers
  • Transparent pricing, compared against AWS on every card
deploy.ts See example
import { Compute } from "@dcs/compute"; const vm = await Compute.deploy({ gpu: "h100-sxm", count: 2, template: "pytorch28", billing: "per-second", }); // instance live in seconds, ssh ready
2× H100-SXM live — billing per second
Consumer GPUs · up to 4× per node
GPUVRAMBest forFrom
RTX 30708 GBSmall 7B LLMs, light inference$0.08/hr
RTX 409024 GB13B LLMs, Stable Diffusion$0.39/hr
RTX A600048 GB30B LLMs, 3D & video render$0.50/hr
RTX 509032 GBHigh-end image & video generation$0.69/hr
Datacenter GPUs · up to 8× per node
GPUVRAMBest forFrom
L40S48 GBImage & video generation at scale$0.90/hr
A10080 GB70B-class LLM inference$1.10/hr
H100 SXM80 GBLarge-model training & inference$1.25/hr
H200 SXM141 GBFrontier-scale modelscontact

A representative slice — the full catalog runs to 47 GPUs. Prices are starting rates; billing is per second.

Start from a ready template, for the workload you have

🔥PyTorch 2.4 🆕PyTorch 2.8 🧩ComfyUI 🐧Ubuntu 22.04 🆕Ubuntu 24.04
🤖
Small LLM7B–13B models — chat, agents, coding
🧠
Large LLM70B+ models — serious inference
🎨
Image generationStable Diffusion, Flux
🎬
3D & video renderrender farms, video pipelines
Earn — put your GPU to work

Your idle GPU, earning quietly

Run AI inference jobs on hardware you already own. Workers earn credits redeemable for cash or build credits — no middleman, no markup, no auction games.

1

Install the worker

One pip command. Python 3.9+, NVIDIA CUDA or Apple Silicon. The worker is fully open source — read every line.

$ pip install dcs-worker
2

Register your machine

One-time login. The worker auto-detects your GPU, picks compatible models and sets a fair earning rate for your hardware tier.

$ dcs-worker login
3

Start earning

Run the daemon and walk away. It heartbeats, polls for jobs, runs inference and submits results — earning while you sleep.

$ dcs-worker start

What your hardware earns

Auto-detected on registration. Rate scales with measured tokens/sec.

TierHardwareVRAMModelsTokens/secCredits/hr
EntryRTX 3060-class12 GB7B~6540
MidRTX 4070 / M3 Pro12–16 GB7B · 13B~11060
HighRTX 4090 / M3 Max24–48 GBup to 30B~180120
DatacenterA100 / H10040–80 GBup to 70B~400+240

1,000 credits ≈ $8.00 · redeem as build credits instantly, or queue a cash payout. A mid-tier GPU at 8 hours/day earns roughly 14,400 credits/month ≈ $115 — best-effort, varies with demand.

Why workers earn more here

Five mechanics, already coded — a network built for operators, not gamblers.

01 / FIVE

Public reliability score

Every worker gets a public 0–100 reputation badge — "98% reliable, 1,240 jobs" — so good workers stand out.

02 / FIVE

Warm-model preference

Workers that already have the right model loaded get prioritised — and paid a warm-pool credit bonus.

03 / FIVE

Worker trust tiers

Reputation buckets workers into Probation → Verified → DCS Trusted. Trusted workers get a higher base rate.

04 / FIVE

Zero-config setup

No Docker, no Kubernetes, no YAML. One pip install and the worker benches itself and starts earning.

05 / FIVE

Un-spoofable capability score

We measure tokens-per-second on a benchmark — faster GPUs earn more, and no one can game a self-reported spec.

REDEMPTION

Two ways to cash out

Convert credits to build credits instantly, or queue a cash payout — bank transfer via Stripe Connect.

What your idle hours could be worth

Move the slider. See your projected earnings.

Pick your hardware tier, drag the slider to how many hours per day your GPU is idle. Real per-tier credit rates from the live network.

8 hrs
credits / day
USD-equiv / day
credits / month
USD-equiv / month

1,000 credits ≈ $8.00. Real per-tier rates from the live network. Earnings vary with demand; redeem instantly as build credits or queue a cash payout (Stripe Connect, rolling out by region).

Wired into real demand, not synthetic load

Every site DCS builds is a job for your GPU.

The Platform routes a share of its build inference through the worker network — so demand is guaranteed, not speculative.

🤖
Platform build Every site = a real inference job
🖥
Compute router Matches the job to a warm worker
Your GPU earns Credits hit your wallet on submit

"Front-of-chain inference" — the Platform routes its own builds through the worker network at traffic weight 0.5-0.7, so workers see real demand from day one, not synthetic load.

Built on the open compute stack

Open standards, no proprietary runtimes

NVIDIA CUDA llama.cpp Hugging Face GGUF Apple Silicon Filecoin lineage Cloudflare + Railway
Shipped & coming

Live in production today — or arriving soon

Transparent about what works now and what's on the way.

Live

NVIDIA + Apple Silicon

Workers auto-detect GPU vendor, VRAM and CUDA version. Consumer cards and Macs are first-class.

Live

Pause & schedule

Pause on battery, set daily windows, whitelist models — the daemon honours your settings.

Live

Realtime balance

Credits and worker state stream to the dashboard — balance ticks up the moment a job submits.

Live

Open-source worker

Every line of the worker daemon is public on PyPI and GitHub — no telemetry, no hidden binaries.

Live

Front-of-chain inference

The Platform routes a share of its build inference through the network — real demand, not synthetic load.

Live

Two redemption paths

Convert credits to build credits instantly, or queue a cash payout via batch processing.

Soon

Stripe Connect payouts

Direct bank transfer in 30+ countries, with per-region KYC and scheduled auto-conversion.

Soon

Org workspaces & caps

Per-member earning caps and concurrent-worker limits — for datacenter operators pooling hardware.

Soon

Filecoin proof of work

Each job's input and output pinned to Filecoin — workers can later prove what they produced.

See it in action

Watch Compute work

Rent a GPU, or put your own hardware to work earning credits.

rent a gpu
$ dcs compute deploy --gpu h100-sxm --count 2 [compute] matching 2× H100-SXM in the catalog… [compute] attaching template — PyTorch 2.8 [compute] provisioning the instance… [compute] per-second billing started
Live — ssh ready in 41s
earn — connect a worker
$ dcs-worker start [worker] detected GPU — NVIDIA RTX 4090 24GB [worker] benchmarking — ~180 tok/s, High tier [worker] rate set — 120 credits / hr [worker] heartbeat ok — polling for jobs…
Online — earning credits while idle
47 GPUsIn the rent catalog
Per-secondBilling — stop any time
H100 / H200Up to 141 GB VRAM
240 cr/hrTop worker earning rate
Open-sourceWorker daemon, public
Works with

The rest of the infrastructure

Compute is the power layer — these products run on top of it.

FAQ

The questions that actually matter

Real questions, answered straight.

How do I get paid — cash or credits?
Both. Credits redeem instantly as build credits inside the Platform, or queue for a cash payout via Stripe Connect (rolling out region by region with per-region KYC). 1,000 credits ≈ $8.00.
Do I need NVIDIA, or does Apple Silicon work?
Both are first-class. The worker auto-detects GPU vendor, VRAM and CUDA version on registration — NVIDIA via CUDA, Apple Silicon via Metal/MLX. Earning rate is benched live, not self-reported.
What runs on my machine?
An open-source Python worker daemon (dcs-worker, public on PyPI and GitHub). It heartbeats, polls for jobs, runs inference, submits results — no telemetry, no hidden binaries.
Can I limit when it runs?
Yes. Pause on battery, set daily windows, whitelist models, cap concurrent jobs. The daemon honours every setting and surfaces them in the dashboard.
What if my GPU sits in a colo or datacenter?
Datacenter operators run the same worker. Org workspaces with per-member earning caps and concurrent-worker limits are shipping for pooled-hardware operators. Stripe Connect payouts handle the org-level KYC.
Is the per-card price competitive vs AWS?
Yes — the catalog table compares every card against AWS list pricing on the same row. Per-second billing means you only pay for what you used; no minimums.
Where is demand coming from — is this just speculative?
It's not. The Platform routes its own build inference through the worker network at traffic weight 0.5-0.7 — every site DCS builds is a real job, not synthetic load.
What if my GPU stops mid-job?
A lapsed heartbeat releases the job back into the queue and another worker picks it up. You don't get credit for incomplete jobs, but you don't lose credit either — and reliability scores reward consistent workers with higher base rates.

Rent a GPU, or earn from yours.

Spin up an instance in seconds — or put idle hardware to work today.

Browse GPUs Start earning