I've spent a lot of time comparing AI models over the past year, but recently one thing caught my attention:
Using Claude Opus at roughly 76% below its official price.
When people discuss AI, they usually focus on benchmarks, reasoning scores, coding ability, or context windows.
But there is another metric that matters just as much:
Performance per dollar.
A model can be incredible, but if the cost limits how often you can use it, its practical value decreases.
With a significant discount, Claude Opus becomes much more interesting for developers, researchers, founders, and anyone running large AI workloads.
The result?
• More experimentation
• Larger projects
• Longer conversations
• More code reviews
• Less concern about usage costs
The AI industry is becoming increasingly competitive, and I think the next major advantage won't come only from having access to the best models.
It will come from knowing how to access and use those models efficiently.
What matters more to you today: absolute model performance or performance per dollar?