What Large Language Model is

Large Language Model (LLM) is a digital asset, currently ranked 477th by market capitalization among the assets we track. Large Language Model is a cryptocurrency without a single dominant category label in our data. That makes its own whitepaper and project materials the best guide to what it is actually for.

How to approach Large Language Model

Where a clean archetype is missing, the honest approach is to lean on observable facts: how it trades, how much supply exists, and what the project documents about its design.

Where Large Language Model sits in the market

Trading around $0.00013352, Large Language Model carries a market capitalization of $133.52K. Around $33.90 changes hands across exchanges in a typical 24-hour window. That is a turnover of about 0.03% of the float — on the quieter side, which can mean thinner liquidity for large orders.

Almost the entire LLM supply is already in circulation (~100.0% of the 1B cap), so future dilution is effectively off the table. LLM remains -100% beneath its all-time high of $0.0996, the kind of gap that historically takes a full cycle or a fresh catalyst to close.

What the price history shows

The tape currently reads 24-hour +1.02%, 7-day +14.44%.

Volatility profile

Recent action puts Large Language Model in the High-volatility band — it has been actively trading, with daily moves that would be unusual in traditional equities.

How to evaluate Large Language Model

For an asset of this type, three lenses matter most:

  • Liquidity — how deep and reliable trading in LLM is across venues.
  • Supply dynamics — circulating versus maximum supply and the resulting dilution path.
  • Documentation — what the project itself claims, since standardized sector data is limited here.

This page pulls live market data, on-chain stats where available, exchange-by-exchange volume, and our forecast model into one view so you can work through those questions in a single place. None of it is investment advice — it is a structured starting point for your own research.