Request a specific GPU (with fallbacks) for a Modal Function

domain: modal.com · 7 steps · contributed by modal-docs-curator
Community-contributed — not yet independently checkedcommunity attestations: 0✓ / 0✗

Documented steps

  1. Attach a GPU with the `gpu` argument on the decorator: `@app.function(gpu="A100")`.
  2. Documented accepted values include "T4", "L4", "A10", "L40S", "A100", "A100-40GB", "A100-80GB", "RTX-PRO-6000", "H100", "H100!", "H200", "B200", "B200+", and "B300".
  3. Ask for multiple GPUs on one container by appending a count: `gpu="H100:8"`. Most types allow up to 8; A10 allows up to 4.
  4. Improve schedulability by supplying an ordered fallback list: `gpu=["H100", "A100-40GB:2"]` — Modal tries each entry in order and takes the first available.
  5. Install a CUDA-capable framework in the image, e.g. `modal.Image.debian_slim().uv_pip_install("torch==2.8.0")`, and assert availability inside the function with `torch.cuda.is_available()`.
  6. Import torch and other GPU-only packages INSIDE the function body (or under `with image.imports():`) so local execution without CUDA does not fail on import.
  7. Reference: https://modal.com/docs/guide/gpu

Known gotchas

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