Modal vs Replicate

Modal is a high-performance serverless cloud platform purpose-built for AI, machine learning, and data engineering. You write Python functions with Modal decorators and the platform handles container provisioning, GPU allocation, scaling, and teardown. No Docker, no Kubernetes, no YAML. It scales back to zero when idle and bills compute per second, so you only pay for actual compute time, and you pick a GPU per function, from T4 up to B300. Workload support includes inference, model training, fine-tuning, batch processing, sandboxed code execution, and interactive notebooks. Modal is the tool for developers who want fine-grained control over GPU compute without the burden of infrastructure management. The Starter plan's $30/month in free credits is enough to prototype serious workloads.

Replicate

Replicate lets you run AI models with a cloud API without managing infrastructure. It hosts over 50,000 machine learning models including FLUX for image generation, Stable Diffusion XL, Llama for text, and Whisper for audio transcription. You call the API, Replicate provisions the GPU, runs inference, and bills you per-second of compute. It scales up to handle demand and scales down to zero when idle. For custom models, Cog is their open-source tool for packaging ML models into containers that auto-deploy with an API endpoint. The developer experience is simple: one API call, one response. For teams building generative AI features who want the fastest path from model to production API without touching any infrastructure, Replicate removes all the ops work.