This study examines how jargon relates to numbers tending to end in zero, or round-number bias, in NFT market pricing. By analyzing 302 unique jargon terms across 3.1 million NFT transactions, we found distinct patterns between language use and pricing to suggest that jargon can drive pricing. Art-oriented terminology strongly correlates with US dollar round-number pricing, while crypto-native terms show different associations. Following this initial evidence, we propose a structural equation model identifying two distinct seller orientations with competing US dollar and Ethereum valuation frameworks. This emerging research suggests how jargon functions beyond descriptions to serve as an indicator of pricing biases in one of two currencies, a topic underexplored in the NFT valuation literature.