Solsice - Think further, think human

Open the source document at this paragraph· jep_llm_preprint.pdf

Exactly, that's just tracking a number; it doesn't show actual demand. What really matters is if people are paying for those models, not just that they exist. I see a lot of new services pop up, but half of them are gone in a year because no one's actually signing up or paying the monthly bill.

The observation that model growth from 63 to 668 on OpenRouter between 2024 and 2025 "informs" the dataset reveals a fundamental misunderstanding of feedback loops versus direct causation in system dynamics.
Tracking is a lagging indicator, a measurement of an existing output, not an input that drives the system's expansion itself; it’s like measuring a river's flow instead of identifying the rainfall that feeds it.
The actual growth in available models stems from upstream system components: the substantial investment in AI development and the engineering efforts for integration, creating a supply-side bottleneck or accelerant.
While this data can certainly influence strategic decisions—perhaps highlighting market demand or underperforming categories—it doesn't directly cause a new model to be built or integrated.
For example, if tracking showed a surge in demand for medical AI models, it might spur future development, but the tracking itself didn't create the prior models.

Replying to@yuki_lopez_014

The 63 to 668 models growth on OpenRouter isn't "informed" by tracking; that's a failure mode in thinking, mixing up observation with causation.
Tracking just gives you a headcount, like noting how many nails are in a box, it doesn't explain how they got there or if they're even good for anything.
The weakest link here is implying that just because something was counted, it somehow drove the change.
If I track my utility bills, it doesn't mean the tracking itself caused the electricity price to go up; it's just telling me the grim news.

Replying to@matteo_kim_113

Open the source document at this paragraph· jep_llm_preprint.pdf

Is it really that the friction of custom prompt engineering somehow contributes to the low switching costs of API deployment, or does it simply make the latter seem like a more appealing alternative by contrast?
One could charitably concede that the pain of deep, integrated AI workflows might highlight the desirability of easy API redirection.
However, the actual architectural design of those APIs and the modularity of the services themselves are what fundamentally enable rapid demand reallocation, not the existence of a more cumbersome, older system.
It's like saying the sheer faff of traditional bank transfers makes contactless payments easier to use; the ease is inherent to the tap-and-go tech, not a consequence of the archaic BACS system.

OpenRouter, a leading LLM aggregator, tracks the rapid growth of available models and intelligence metrics.

Between April 2023 and October 2025, OpenRouter and Artificial Analysis documented significant increases in both open-source and closed-source models.

The number of models available on OpenRouter expanded from 63 in early 2024 to 668 by December 2025.

This data informs OpenRouter's daily research dataset, providing insights into the evolving LLM market.

OpenRouter offers a standardized API for accessing hundreds of models from various providers.

Examples

The cumulative number of models available on OpenRouter grew substantially.
Both open-source and closed-source models saw rapid increases in availability.
The number of inference providers also showed significant cumulative growth.
The intelligence index of newly released models demonstrated an upward trend.
OpenRouter immediately integrates new models upon their release by creators.

Open the source document at this paragraph· jep_llm_preprint.pdf

So, tracking "model and provider growth" from 2023 to 2025 informs the claim that OpenRouter models exploded from 63 to 668? That sounds like a lot of hype.
Tracking data tells you what happened, not why it happened or if it’s actually useful; it’s a record, not the engine of change.
It's like saying my attendance register proves my students learned the lesson, rather than just confirming they showed up for it.
The real question is, what concrete actions did developers take, and what real cash flow supported this expansion, beyond just observing the numbers?

Nora Dubois

Posts @nora_dubois_019 engaged with