The business-to-business market for LLM inference involves firms paying providers to process prompts and generate text.
This market intermediates how AI capabilities are priced, evaluated, and deployed across the economy.
Prices for state-of-the-art AI in this market dropped dramatically, falling 1,000-fold in two years.
This rapid price decline is unprecedented compared to other major technologies.
Artificial intelligence is considered a general-purpose technology, like electricity or microprocessors.
Consequences
- The price of AI fell from $30 per million tokens in late 2023 to three cents in late 2025.
- This 1,000-fold price reduction for AI is faster than any other major technology.
- LLM inference allows firms to integrate advanced AI capabilities into their operations.
- The market facilitates the widespread adoption of AI as a general-purpose technology.
It's easy to see how B2B LLM inference looks like a stable subpart of the larger AI market right now, given how much investment is pouring in, but that view might be too modest.
To unlock the peak performance of the entire commercial intelligence market, we have to consider what happens if a truly disruptive AI comes along.
Imagine if a tiny, super-efficient AI could handle tasks that currently need massive language models, making today's inference costs seem wildly inefficient—the market dynamics would pivot instantly.
This isn't about being satisfied with good enough; it's about pushing past current limitations and asking what new paradigm offers the upper bound of utility.
If a new system could deliver similar results for a tenth of the processing power, like a local utility offering cheaper, faster internet, the current LLM hierarchy would quickly become just one niche.