Trained on transactions. Judged by what the market paid. LLMs predict the next token. The LPM predicts the next price.
LLMs predict the next token. The LPM predicts the next price. Same mathematical core. Different objective. Language models are trained on text and judged by humans; the LPM is trained on transactions and judged by the market.
Generation is the easier problem — the model produces text; whether it's good is a human judgment. Pricing is harder. The model produces a number, and whether that number is right is decided by the market — by whether someone pays for it. There is a settlement.
Every piece of content the network knows about — being repriced. Some refreshs every two seconds, others once a minute. Each at its own frequency.
| Title · Brand | Event Impact | Quote | LPM | Freq | Demand | Change |
|---|
The function is non-monotonic. The same article can be worth $0.10 on Tuesday and $40 on Wednesday.
Black-Scholes turned options into an asset class. The Large Pricing Model turns information into one. The underlying changes — from a contract on a stock to a sentence, an article, a video, a dataset. The principle holds: a price, marked continuously to live supply and demand.
State tensor in. Four genomes decompose. The policy network fires across 300 to 30,000 comparables. The model outputs a bounded price. Then it runs again — every 0.8 to 1.2 seconds.
Each quote includes a forward forecast with an explicit, empirically calibrated confidence interval. The interval widens with horizon — a few basis points at the next tick, several percent at five minutes.
The reasoning is exposed. The weights stay sealed. Every quote ships with the evidence behind it — the comparables it leaned on, the reliability of the model state, the events shaping the moment.
An LLM tells you what the world might say.
The LPM tells you what the world is willing to pay.
Each with its own genome, its own market behavior, its own pricing curve. The LPM runs continuously across the network — quoting, anchoring, repricing. Trillions of interactions, every day.
The weights tune themselves.
No human touches them.
At this speed, none could.