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Abstract: Precise estimation of biomass at a regional scale is required for evaluating forest carbon stocks throughout the Amazon. We examined six types of allometric models to identify the best estimator of biomass in primary forests (terra firme) in the northwestern sector of the Brazilian Amazon. We also tested six regression models for estimating tree height. We developed each allometric model using measurements of 101 trees excavated in a primary forest distributed along the upper Rio Negro. A simple power function with stem diameter at breast height D as a single variable was selected as the best model for estimating each biomass component, i.e. above-ground total mass AGW, below-ground total mass BGW, and whole individual mass. Among models developed to estimate tree height H from D, we selected a regression model with a coefficient corresponding to an asymptotic height as the best fit. The D–AGW relationship at our study site differed significantly from models developed previously for other regions of the Amazon. We explain this regional variation in part by regional differences in D–H relationships of sample trees. The D–BGW relationship at our site also differed significantly from that in the central Amazon. However, AGW–BGW relationships were consistent between the upper Rio Negro forest and other forests in the central Amazon, in that the BGW–AGW ratio was constant as 0.136 regardless of tree size. On the basis of D-based allometry and census data from 23 plots established in the upper Rio Negro region, we estimated a stand-level total biomass (dry mass) of 252.6Mgha−1. This estimate is at least 73% lower than the potential stand biomass for the region previously suggested by several meta-analyses. [Copyright &y& Elsevier]