Modal

Modal is a serverless cloud platform that lets developers run code, AI models and data-intensive jobs in the cloud — including on GPUs — by defining their infrastructure directly in Python, with no servers or containers to manage. It's built for the era of AI and heavy compute, making it remarkably easy to take a Python function and run it at scale in the cloud, whether that's serving a model, training, processing data, or running batch jobs, all while only paying for the compute you actually use.

The developer experience is Modal's standout quality. You write normal Python, decorate functions to specify the resources they need (CPU, memory, GPUs, dependencies), and Modal handles provisioning, containerization, scaling and execution behind the scenes. There's no Dockerfile wrangling, no Kubernetes, no idle servers — you just run your code in the cloud as if it were local, and it scales from zero to thousands of containers automatically. This dramatically lowers the barrier to running serious compute, especially GPU workloads that are otherwise painful and expensive to manage.

This makes Modal especially popular for AI and data use cases: serving and fine-tuning models, running inference at scale, generating images or audio, processing large datasets, web scraping, and scheduled jobs. Its serverless, pay-per-use model means you're not paying for idle GPUs, which is a major cost advantage for spiky AI workloads. Teams and individual developers alike use it to move fast without building infrastructure expertise. As AI and compute-heavy applications proliferate, a platform that makes powerful cloud compute as easy as writing Python is genuinely valuable. For developers who want to run code, models and data jobs in the cloud — including on GPUs — with minimal friction and no infrastructure management, Modal offers an elegant, powerful and increasingly beloved solution.