CI that runs on real GPUs
Run your GitHub Actions on A100s and H100s with a one-line change. Isolated, ephemeral runners spin up on demand, and Gauss manages the hardware, drivers, and capacity for you.
From ubuntu-latest to H100 in one commit
Gauss plugs into the CI you already have, with nothing to install or operate.
- Change one line
- Point runs-on at a Gauss label. Your workflows, secrets, matrices, and required checks stay as they are.
- We spin up the GPU
- An isolated runner boots in under thirty seconds with the driver and CUDA toolchain in place. You skip the queue and the capacity planning.
- Results land in your PR
- Tests, benchmarks, and regression checks report back to GitHub like any other job. When the job finishes, Gauss destroys the runner.
.github/workflows/benchmark.ymldiff
jobs: benchmark: runs-on: ubuntu-latest runs-on: gauss-h100 steps: - uses: actions/checkout@v4 - run: make benchBuilt for GPU software teams
Reliable hardware signal, inside the workflow your team already trusts.
- On-demand accelerators
- A100s, H100s, and B200s available the moment a job starts. Billing stops the second it ends.
- H100 SXM80GB HBM3·82%A10080GB HBM2e·64%B200192GB HBM3e·41%
- Ephemeral by design
- Every job gets a fresh, isolated runner that Gauss destroys on completion. Nothing carries over between runs.
- Provision18sRun job4m 12sDestroyNothing persists
- Native GitHub Actions
- Gauss runners behave like any other label. Your checks, matrices, and secrets work unchanged.
- benchmarkgauss-h1004m 12scompatgauss-a1002m 58skernelsgauss-h1006m 03s
- Regression detection
- Benchmark on identical hardware every run, so you catch a performance regression in the PR before it ships.
- attn_fwd latency+38%
Flagged at 7c3f2a1, before it reached main.
Get early access
We onboard teams in small waves so setup gets real attention. Tell us what you'd run and we'll reach out when your spot opens.
No spam. If your CI runs on GitHub Actions today, you're ready.