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Recently there has been renewed interest in accurate estimation of forest carbon stock in the context of climate change mitigation in the forestry sector. Many studies were carried out focusing on ground measurements and remote sensing techniques for the improvement of above ground biomass estimation at plot and landscape scales. However most studies neglected the importance of above ground biomass (AGB) model selection. Our study aims at assessing existing models for estimating tree height and AGB in tropical peat land forest. We use destructive sampling data as reference value. In August 2014, ten trees from mixed species and maximum diameter of 94 cm were cut down and measured in a peat swamp forest of Central Kalimantan, Indonesia. We evaluated existing regional and local equations for tree height and AGB estimation. We found that all existing models showed mean absolute errors between 28% to 83% and 19% to 51% for tree height and AGB models, respectively. Tree height models tends to over- or under-estimate the reference values. Moreover, the use of tree height model into AGB model propagates these errors further into the AGB estimates. We also found that regional AGB model, which developed using datasets from Kalimantan and Sumatra, outperformed other local equations. These findings suggest that existing tree height and AGB models should only be used if cautiously validated through data, in particular for the tree height models which are used as a basis for the AGB.