The Hidden Costs of a Dedicated GPU

When you rent a GPU instance from a major cloud provider, you're not just paying for the time your model is running. You're paying for every second the machine is on. For an application with variable or infrequent traffic, that means you could be paying for an expensive GPU that is idle 95% of the time.

Let's do the math on a typical g4dn.xlarge instance from AWS, which costs roughly $0.526 per hour. That's nearly $380 per month, whether you run one inference or one million.

The Serverless Advantage: Pay Only for What You Use

Ignition-Hub's model is different. We maintain a large, multi-tenant pool of GPUs. When your API call comes in, we route it to an available GPU, run your model for the required 50-100 milliseconds, and bill you *only* for that execution time. When you have no traffic, your cost is zero.

For a startup with 100,000 inference requests per month, each taking 100ms, the total GPU time is only about 2.7 hours. Compared to the 720 hours you'd pay for a dedicated instance, the savings are astronomical. Our platform handles the complexity of scaling, allowing you to benefit from enterprise-grade hardware without the enterprise-grade price tag.