This paper addresses the problem of real time 3D modeling from images with multiple cameras. Environments where multiple cameras and PCs are present are becoming usual, mainly due to new camera technologies and high computing power of modern PCs. However most applications in computer vision are based on a single, or few PCs for computations and do not scale. Our motivation in this paper is therefore to propose a distributed framework which allows to compute precise 3D models in real time with a variable number of cameras, this through an optimal use of the several PCs which are generally present. We focus in this paper on silhouette based modeling approaches and investigate how to efficiently partition the associated tasks over a set of PCs. Our contribution is a distribution scheme that applies to the different types of approaches in this field and allows for real time applications. Such a scheme relies on different accessible levels of parallelization, from individual task partitions to concurrent executions, yielding in turn controls on both latency and frame rate of the modeling system. We report on the application of the presented framework to visual hull modeling applications. In particular, we show that precise surface models can be computed in real time with standard components. Results with synthetic data and preliminary results in real contexts are presented.