Quick answer

RunPod rents raw GPU pods and serverless endpoints at some of the lowest prices available; you manage the software. Modal is a serverless platform where you write Python functions and it handles containers, GPUs, and scaling. Baseten is managed model inference with performance tooling and enterprise features. Fine-tuners and hobbyists lean RunPod, developers shipping endpoints lean Modal, and companies serving production models at scale lean Baseten.

There are three reasons to rent a GPU rather than call a hosted model API: you are training or fine-tuning, you are running a model no API offers, or your volume is high enough that owning the inference is cheaper. Which platform fits depends on which of those you are doing.

RunPod: cheapest raw compute

RunPod sells GPU time by the second, from consumer cards to H100-class hardware, on secure or community tiers. You pick a template (Stable Diffusion, vLLM, Ollama, a bare CUDA image), attach a network volume, and you have a machine. Serverless endpoints scale to zero for inference. Prices are among the lowest in the market. The trade-offs are that availability of popular GPUs fluctuates, community-tier reliability varies, and everything above the driver is your responsibility.

Modal: serverless Python

Modal asks you to decorate a Python function with the GPU it needs and deploys it. Containers build from code, scale with traffic, and bill per second of use. It is the platform developers describe as "feels like magic" because there is no Docker, no cluster, and no idle cost. It is priced above RunPod per GPU-second, which is the fee for the developer experience, and it is Python-centric.

Baseten: managed inference

Baseten focuses on serving models in production: an optimised inference stack, autoscaling, observability, and enterprise controls such as dedicated deployments and compliance. Its Truss framework packages models, and the platform tunes for latency and throughput. It costs more than raw compute and is aimed at teams whose model is a product, not an experiment.

Rough cost logic

  • Experiments and fine-tuning runs of a few hours: RunPod, by a wide margin
  • Low-traffic inference that must scale to zero: Modal or RunPod serverless
  • Steady high traffic: dedicated capacity on any of the three beats serverless; compare per-hour prices
  • Popular open models: a hosted API from Together, Fireworks, or Groq is usually cheaper than running it yourself until volume is large

Related reading

Replicate vs Fireworks vs Baseten What is AI inference? What is serverless inference?

Bottom line

RunPod for the cheapest GPUs, Modal for the nicest developer experience, Baseten for production serving with support. Before any of them, check whether a hosted API already serves your model; for most teams that is cheaper until they are large.