Find the right GPU cloud for what you actually want to run.
Compare GPU providers for AI video, image generation, LLMs and training — without decoding enterprise cloud jargon.
AI image generation
LLM inference
Model fine-tuning
Bursty production API
Experimenting and testing
Start with what you want to run
GPU hosting providers
Filter by what you want to run, rather than by infrastructure terminology.
fal
Image, video and audio model APIs, serverless GPUs and dedicated compute for model development.
Modal
Serverless GPU compute for model inference, fine-tuning, training and evaluation.
Replicate
Hosted APIs for image, video and language models, with fine-tuning and custom deployments.
Pod or serverless?
For most people, this is the first decision that matters.
GPU Pod / VM
A GPU machine stays allocated to you while it is running.
- Best for steady or continuous work
- Predictable environment
- You pay while the machine is running
- Concurrent jobs usually need your own queue/workers
Serverless GPU
Workers spin up for jobs and scale with demand.
- Best for bursts and unpredictable traffic
- Multiple requests can scale across workers
- You mainly pay for execution time
- Cold starts can matter
What does one generation actually cost?
Hourly rates are hard to compare. Convert them into an approximate cost per image, video or inference job.
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