Token price reductions follow a Jevons paradox pattern, where a 10x price drop leads to a >10x increase in usage, as demonstrated by OpenAI's GPT 5.6 Luna model.
Alex Atallah uses the example of OpenAI's GPT 5.6 Luna model to illustrate the Jevons paradox in AI: a 10x price reduction led to a 13x surge in usage, meaning lower prices expand the total market rather than shrink the revenue pie. ✦ AI generated
Alex Atallah · 20VC · 2026-08-10 · original ↗
starts at this moment · 21:14
“Okay, we we've seen token prices fall 90% in like 18 months. Is the reduction of token prices helpful or hurtful to your business? Cuz obviously you have a take on spend. If they come down and spend is more efficient, seemingly it's bad for your business. You have a shrinking pie to to take from.”
Well, so a lot of people talk about the Jevons paradox that, you know, when when uh prices go down by 10x, the usage increases by more than 10x... For example, uh GPT 5.6 Luna on OpenRouter. Um OpenAI cut prices by 5x and then in coordination with us by another 2x. So in total, prices the price of Luna has dropped 10x on OpenRouter over the last 2 weeks. And guess how much usage has grown? 13x. So it's a close to perfect Jevons paradox story where you drop prices 10x and usage grows by more than 10x. Um just a bit more. And uh and the also the the usage is pretty stable.
verbatim transcript · starts at 21:14
21:14Jevons paradox that, you know, when when uh prices go down by 10x, the usage increases by more than 10x. Um but like no one has really done a great job modeling it. There We do have a lot of spot stories that confirm it. For example, uh GPT 5.6 Luna on OpenRouter. Um OpenAI cut prices by 5x and then in coordination with us by another 2x. So in total, prices the price of Luna has
21:51dropped 10x on OpenRouter over the last 2 weeks. And guess how much usage has grown? 13x. So it's a close to perfect Jevons paradox story where you drop prices 10x and usage grows by more than 10x. Um just a bit more. And uh and the also the the usage is pretty stable. Like it like grew, you know, it like flattened out but at at 13x and then you
22:24know, it's been kind of like growing at the same rate that it was growing before it hit the the 13x multiple. Um so that's pretty interesting and it's a pretty like uh low variable like there are there are there are few other confounding variables in the story and and it was also done in the middle of DeepSeek launching and having a really really good price and GLM having a
22:48really good price. Like now Luna is being used more than GLM on OpenRouter. GLM used to be like one of the top like three four models by token volume and now Luna is past it. This is the first time OpenAI has had a model on our platform in the top you know, three to five models by token volume in a extremely long time. So, this was a really big and interesting
23:15move. >> How reflective of the market are your token volumes? Cuz it's about I I may get this wrong, but maybe 1 and 1/2 2% of say token volumes. And so, how reflective are they? Because a lot of people when I say, "Oh, the top five models when I look at Open Router are all Chinese." What does that mean? They'll go, "Oh, well, Harry, no offense to Open Router,
23:36but like it's not reflective of the market and most people who use Frontier, it doesn't go through that." Like they use Frontier APIs and so it's not counted. To what extent are your rankings reflective of true token usage? >> We try to estimate how they're off um by you know, just surveying people sometimes or looking at like the surveys other people have done. Um I think we we have