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State of AI: An Empirical 100T Token Study with OpenRouter

openrouter.ai

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Re: State of AI: An Empirical 100T Token Study with OpenRouter

#11

Post by maikakz »

lukev wrote: post #9

Super interesting data. I do question this finding: > the small model category as a whole is seeing its share of usage decline. It's important to remember that this data is from OpenRouter... a API service. Small models are exactly those that can be self-hosted. It could be the case that total small model usage has actually grown , but people are self-hosting rather than using an API. OpenRouter would not be in a pos…

Thank you & totally agree! The findings are purely observational through OpenRouter’s lens, so they naturally reflect usage on the platform, not the entire ecosystem.

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#12

Post by raincole »

syspec wrote: post #8

According to the report, 52% of all open-source AI is used for *roleplaying*. They attribute it to fewer content filters and higher creativity. I'm pretty surprised by that, but I guess that also selects for people who would use openrouter

If you rely on AI to write most of your code (instead of using it like Stackoverflow), Claude Code/OpenAI Codex subscription are cheaper than buying tokens. So those users are not on openrouter.

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#13

Post by djfergus »

syspec wrote: post #8

According to the report, 52% of all open-source AI is used for *roleplaying*. They attribute it to fewer content filters and higher creativity. I'm pretty surprised by that, but I guess that also selects for people who would use openrouter

Openrouter has an apps tab. If you look at the free, non-coding models, some apps that feature are: janitor.ai, sillytavern, chub.ai. I'd never heard of them but people seem to be burning millions of tokens enjoying them.

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#14

Post by ribosometronome »

themanmaran wrote: post #2

> The metric reflects the proportion of all tokens served by reasoning models, not the share of "reasoning tokens" within model outputs. I'd be interested in a clarification on the reasoning vs non-reasoning metric. Does this mean the reasoning total is (input + reasoning + output) tokens? Or is it just (input + output). Obviously the reasoning tokens would add a ton to the overall count. So it would be interesting t…

As would models that that are overly verbose. My experience is the Claude tends to do more than is asked for (e.g. immediately move on to creating tests and documentation) while other models like Gemini tend to be more concise in what they do.

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#16

Post by djfergus »

asadm wrote: post #10

Who is using grok code and why?

It's a 1.7 trillion token free model. Why wouldn't you try it?

I've been testing free models for coding hobby projects after I burnt through way too many expensive tokens on Replit and Claude. Grok wasn't great, kept getting into loops for me. I had better results using KAT coder on opencode (also free).

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#18

Post by djfergus »

raincole wrote: post #12
syspec wrote: post #8

According to the report, 52% of all open-source AI is used for *roleplaying*. They attribute it to fewer content filters and higher creativity. I'm pretty surprised by that, but I guess that also selects for people who would use openrouter

If you rely on AI to write most of your code (instead of using it like Stackoverflow), Claude Code/OpenAI Codex subscription are cheaper than buying tokens. So those users are not on openrouter.

I'm curious what percentage of claude/codex users this is true for - I assumed their business models rely on this not being true for the majority.

Re: State of AI: An Empirical 100T Token Study with OpenRouter

#20

Post by skywhopper »

This is interesting, but I found it moderately disturbing that they spend a LOT of effort up front talking about how they don’t have any access to the prompts or responses. And then they reveal that they did actually have access to the text and they spend 80% of the rest of the paper analyzing the content.
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