Modal

Freemium

Modal is a serverless cloud platform for running AI and ML workloads on GPUs. You write Python code, add a decorator, and deploy without touching Docker or Kubernetes.

It handles the infrastructure: GPU provisioning, scaling from zero to thousands of GPUs, and per-second billing. You pay only when code runs.

Modal sits in Developer Tools. It is built for teams that need custom pipelines, not pre-built APIs.

Open it if you want code-first GPU infrastructure without DevOps overhead. Skip it if you need managed AI endpoints or steady, always-on workloads.

It fits when your work does not match pre-built solutions.

• Bursty, unpredictable GPU workloads: You scale to zero between jobs. You do not pay for idle GPUs.
• Teams wanting code-first model serving: You write Python with GPU decorators. You skip container management entirely.
• ML engineers training custom models: You run multi-GPU fine-tuning and distributed training. You build what you need.
• Solo developers and small teams: You ship AI features without hiring infrastructure engineers.
• AI developers who want serverless GPU: You deploy Python functions. You avoid DevOps overhead.
• Rapid prototyping and ML experiments: You test ideas fast. You iterate without waiting on cluster setup.
• Teams with unique GPU workloads: Your needs do not fit pre-built APIs. You need arbitrary Python execution.
• Research pipelines: You run reinforcement learning rollouts and isolated code execution. You control the environment.

These are what you notice after running a few workloads.

• Sub-second cold starts: GPU containers start fast. You keep users happy on interactive workloads.
• Scale-to-zero billing: You pay by the second. You stop paying when code stops.
• Python-native infrastructure: You define everything in code. You skip YAML, Dockerfiles, and Terraform.
• Simple GPU access: You add one decorator flag. You get A100, H100, or H200 without quotas.
• Secure sandboxes: You run untrusted code in isolation. You build coding agents safely.
• $30 monthly free tier: You test before you commit. You compare against Colab and Kaggle limits.

You move from local code to running GPUs in minutes.

1. Install the Modal SDK and authenticate.
2. Write a Python function and add the @app.function(gpu="A100") decorator.
3. Run modal serve to test your function live.
4. Deploy with modal deploy to get a persistent endpoint.
5. Watch logs and scale in the Modal dashboard.

Skip it when the tradeoffs do not fit your work.

• Expensive at steady utilization: You run GPUs all day. Costs exceed dedicated GPU clouds.
• Zero pre-built AI endpoints: You need image generation APIs today. You build everything from scratch.
• No self-hosting option: You want to run on your own hardware. You are locked to Modal's infrastructure.
• Verification and billing friction: You are an international user. Payment setup may fail repeatedly.
• Limited to isolated functions: You need full-stack apps with frontends and databases. Modal handles only compute.
• Vendor lock-in via decorators: You migrate later. Your code is tied to Modal-specific syntax.