cirun

GPU runner

NVIDIA V100 runners for GitHub Actions

Volta-era training GPU. Lives on in regulated and on-prem environments. Cirun spins NVIDIA V100 VMs up on your cloud account per workflow — pick whichever cloud has the SKU on your existing account, CUDA + drivers come from each cloud's own Deep Learning image.

Run a workflow on NVIDIA V100 Docs

Why this fits

  • 16 GB VRAM and ~125 TFLOPS FP16 — inference smoke tests, fine-tune sanity checks and per-PR GPU regressions.
  • Works with PyTorch, TensorFlow, CUDA 11.x stacks — CUDA + drivers come from your cloud's official Deep Learning AMI / image, not your workflow.
  • Ephemeral by default — each job gets a clean VM, so leaked weights or hung CUDA contexts can't poison the next run.

.cirun.yml

.cirun.yml
1runners:
2  - name: gpu-v100
3    cloud: azure
4    instance_type: Standard_NC6s_v3
5    # Use Microsoft's HPC/DSVM Ubuntu image for pre-installed CUDA +
6    # drivers.
7    machine_image: microsoft-dsvm:ubuntu-hpc:2204:latest
8    labels:
9      - cirun-gpu-v100

Drop this in your repo root. The first workflow that requests the runner label spins this configuration up on your cloud account.

Where you can run it

Azure Standard_NC6s_v3
6 vCPU · 112 GiB host

Ready to run your CI here?

Cirun is free for open source. For private repos, flat monthly plans by repo count — never per CI minute.

Run a workflow on NVIDIA V100 Docs

Sources · verified 2026-05-25