GPU compute for teams, without owning hardware

Contributor AI gives you a pool of distributed GPUs for inference, fine‑tuning and batch jobs. You focus on models and data — we handle capacity and contributors.

How to start as a client

  1. 1. Create a client account. Use your work email so we can verify your company if needed.
  2. 2. Create your first job. Describe the workload, upload config or image, set priority and budget cap.
  3. 3. Watch the job run. We schedule it across suitable contributors and show live status in the dashboard.
  4. 4. Download results and logs. When done, you can fetch outputs via UI or API and review logs.
  5. 5. Scale out. Add more jobs or integrate our API into your pipelines and CI.

Pricing model

  • • You are billed per GPU‑hour, plus storage and network where applicable.
  • • You can set a hard budget per job; tasks stop when the limit is reached.
  • • Higher priority queues reserve more capacity during busy periods.
  • • Volume discounts and dedicated capacity are available for long‑term usage.

Prices aligned with Vast.ai, RunPod, Lambda Labs — competitive GPU cloud rates.

GPU pricing (per hour, USD)

Competitive with Vast.ai, RunPod and other GPU marketplaces.

GPUVRAM$/hr
RTX 306012 GB$0.22
RTX 308010 GB$0.38
RTX 409024 GB$0.55
A10040 GB$0.58

Full client guide

Open guide →

For clients — step by step

You do not need Tailscale — only a browser. For jobs to run, the platform operator sets up Tailscale between the server and the GPU PC. Full guide: /tailscale Tailscale setup

  1. 1. Sign up as Client

    Open Sign up → choose Client. Sign in at gpugrid.duckdns.org.

  2. 2. Top up balance

    Dashboard → My jobs → Top up. Demo top-up adds USD to your account (no card yet).

  3. 3. Create a job

    New job → Title + Description. Put lyrics in Description (Verse/Chorus tags work). Set budget (USD). Submit.

  4. 4. Wait for the GPU

    Status pending → running → completed (usually 3–15 min for audio). Page refreshes every 8 seconds.

  5. 5. Get the result

    When status is completed, download MP3 via API: GET /api/tasks/{taskId}/artifact (Bearer token from Sign in).

FAQ

Why does the site say Remote GPU offline?
ACE-Step is not running on the PC, or Tailscale is disconnected. Start acestep-api and check Tailscale on both devices.
Do I need a contributor if the platform has remote GPU?
Jobs can run on the platform's connected PC automatically. Contributors are for extra capacity and other machines.
What task types are supported now?
Audio generation with lyrics via ACE-Step (ace_step_audio). More GPU task types coming later.

Who is this for?

  • • Product teams running LLM and vision inference in production.
  • • Data science groups with spiky training workloads.
  • • Agencies and studios that occasionally need a lot of GPU power.