Bring your own capacity

OpenRelay · Bring your own capacity

We run your GPU fleet for nothing, and pay you for the hours it sits idle.

WEEKENDFleet capacity you already pay forMonTueWedThuFriSatSun100%0%one training run saturates SaturdayYour teamsIdle. Every hatched second is one we serve inference on and pay you for.69% average utilization.The other 31% of your GPU-hours is what earns.hourly · one week · a fleet nobody would call underused

What it costs

Nothing. No platform fee, no per-node charge, no support tier.

How we make money

We serve inference on your idle hours and take a share. You take the rest.

Where it runs

On-prem, colo, or reserved instances in your own cloud account.

Network changes

Nothing inbound. Nodes dial out over QUIC, so egress needs HTTPS and UDP 443.

What your team gets

KubernetesLive
SlurmRolling out
GPU VMsLive
PodsLive
EndpointsLive

Idle capacity

nothing to configure

There is no switch to flip and no policy to write. A chip nobody on your side is using picks up inference, and the moment your team wants it back it is theirs again, near-immediately.

What we operate

Included · $0

  • Security patching, with the kernel held so apt cannot reboot a node under a running job
  • GPU health checks, with unhealthy cards delisted before they can fail a job
  • Node agent updates on a jittered timer, so the fleet never restarts at once
  • VFIO binding and IOMMU config, boot-persistent across reboots
  • Base image and VM template distribution, content-addressed and checksum-verified
  • Scheduling, routing, and metering per user and per project
  • The reconciliation that cleans up after all of it

What you see

app.openrelay.inc/fleet

Nodes onboarded

24

3 sites

Your utilization

69%

trailing 7 days

Idle hours served

1,284

this month

NodeGPUsRunningUtilization
gpu-ord-018x H100vision-lab / train-7bKubernetes98%
gpu-ord-028x H100vision-lab / train-7bKubernetes97%
gpu-ord-038x A100nlp / eval-sweepPod62%
gpu-ord-044x L40Splatform / ci-runnersVM31%
gpu-sfo-018x H100OpenRelay inferenceEarning88%
gpu-sfo-028x H100OpenRelay inferenceEarning91%
Illustrative. Sample fleet, sample numbers.

Onboarding

  1. 01

    Run one command on a clean Ubuntu install.

  2. 02

    The node dials out and reports its GPUs and topology.

  3. 03

    Your teams schedule against it.

  4. 04

    Idle hours start earning, with nothing to configure.

Requirements: x86_64 with IOMMU, 32 GB RAM or more, NVMe, a clean Ubuntu install, outbound HTTPS and UDP 443.

Tell us the GPU models, the node count, and roughly how busy they are, and we will come back with what the fleet earns.