Insight
AI Training vs Inference: Where the AI Industry Is Competing Now
Key Points
- Training builds models; inference runs them.
- Inference demand grows every time AI is used.
- Cost per useful task is becoming a major metric.
Training vs inference
Training is the process used to create or improve an AI model. Inference begins when that trained model is put to work on a new input.
Why inference matters
One inference request may be inexpensive. Billions of them are not.
Agents change the economics
Agents can make repeated model calls, use tools and work through multiple steps, increasing compute use.
Why smaller models matter
Not every request requires the most capable model. Routing can send routine tasks to smaller systems.
Why It Matters
The economics of AI are shifting from how much it costs to build a model toward how much useful work that model can perform for a given amount of compute.