State of AI: An Empirical 100T Token Study with OpenRouter
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Re: State of AI: An Empirical 100T Token Study with OpenRouter
#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 to see it on an apples to apples comparison with non reasoning models.
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#3This is really amazing data. Super interesting read
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#4> 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…
I'm out of time but "reasoning input tokens" from fortune 5000 engineers sounds like a lobotomized LSD dream, would you care on elaborating how you distinguish between reasoning and non-reasoning? vs "question on duty"?
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#5> 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…
I'm out of time but "reasoning input tokens" from fortune 5000 engineers sounds like a lobotomized LSD dream, would you care on elaborating how you distinguish between reasoning and non-reasoning? vs "question on duty"?
I believe they’re just classifying all models into “reasoning models” eg o3 vs “non reasoning models” eg 4o and just doing a comparison of total tokens (input tokens + hidden reasoning output tokens + shown output tokens)
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#6> 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…
I'm out of time but "reasoning input tokens" from fortune 5000 engineers sounds like a lobotomized LSD dream, would you care on elaborating how you distinguish between reasoning and non-reasoning? vs "question on duty"?
"reasoning" models like GPT 5 et al do a pre-generation step where they:
- Take in the user query (input tokens)
- Break that into a game plan. Ex: "Based on user query: {query} generate a plan of action." (reasoning tokens)
- Answer (output tokens)
Because the reasoning step runs in a loop until it's run through it's action plan, it frequently uses way more tokens than the input/output step.
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#7Earlier quoted context omitted.
I'm out of time but "reasoning input tokens" from fortune 5000 engineers sounds like a lobotomized LSD dream, would you care on elaborating how you distinguish between reasoning and non-reasoning? vs "question on duty"?
I believe they’re just classifying all models into “reasoning models” eg o3 vs “non reasoning models” eg 4o and just doing a comparison of total tokens (input tokens + hidden reasoning output tokens + shown output tokens)
that's exactly right!
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#8According 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
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#9Super 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 position to determine this.
Re: State of AI: An Empirical 100T Token Study with OpenRouter
#10Who is using grok code and why?