Modal Compute

Use the modal CLI for serverless GPU workloads. No pod lifecycle to manage — write a decorated Python script and run it.

Setup

pip install modal
modal setup

Commands

GPU types

T4, L4, A10G, L40S, A100, A100-80GB, H100, H200, B200

Multi-GPU: "H100:4" for 4x H100s.

Script pattern

import modal

app = modal.App("experiment")
image = modal.Image.debian_slim(python_version="3.11").pip_install("torch==2.8.0")

@app.function(gpu="A100", image=image, timeout=600)
def train():
    import torch
    # training code here

@app.local_entrypoint()
def main():
    train.remote()

When to use

• Stateless burst GPU jobs (training, inference, benchmarks)
• No persistent state needed between runs
• Check availability: command -v modal