my AI <> crypto thesis is increasingly skewed towards a market for inference

models are commoditizing so the gap between them is narrowing, open-source is getting better, and apps increasingly route between multiple models rather than depend on just one

that changes where value can accrue

if intelligence becomes abundant, the scarce commodity then becomes access and execution, who serves the inference, at what price, with what latency, capacity and privacy guarantees

today, that market is fragmented across closed APIs, GPU networks, credits and idle capacity. there is essentially no common pricing, liquidity or settlement

so i see three layers emerging:

1) decentralized intelligence, $TAO, markets for producing intelligence
2) private inference, $VVV, $ROUTER, $POD, accessing intelligence without sharing data
3) inference markets, $ORBIO, $MANY, @idleaixyz, markets for pricing, routing, settling and eventually trading intelligence itself

i am most intrigued by the last category.

so while agents become the dominant buyers of that commodity, they won’t care which LLM serves the request, they will want to optimize for price, quality, latency, privacy and availability.

that pushes inference from just fixed-price APIs → competitive markets.

and if inference becomes a commodity, the largest opportunity may not be another AI model.

it may be the market infrastructure where intelligence gets priced and traded.

below are some projects and tokens that i believe will lead thier category.

https://x.com/arndxt_xo/status/2101728307289178127