colloid surface must change when the colloid moves. Because the solute moves with the fluid, such a configurational change can only be achieved if there is a surface slip velocity. As discussed by Golestanian et al [11, 12], the colloid velocity can be expressed as the integral over the colloid surface of a slip velocity v$_{s}$ = − µ ∇ c where c is the solute concen- tration, µ the surface mobility µ = k$_{B}$T λ $^{2}$/η , η being the viscosity and λ a length-scale. In the non-permeable case, the latter is the Derjaguin length, describing the range of interac- tions between the colloid and solute. The length-scale λ is then small, so that the linearised theory predicts that chucking will have little effect on colloidal motion. However, Adjari and Bocquet [26] have shown recently that for solutes smaller than the intrinsic slip length, a small degree of surface slip can lead to large enhancements of λ . Moreover, for colloids that are partially or fully permeable to solvent (osmiophoresis), anything between this result and a much larger colloid velocity, equal to the “naive” kinetic force f = − k$_{B}$T ∫ ˆ n cdS multiplied by a mobility factor, is possible [12, 27]. The motion of a semi-permeable rigid vesicle in response to a solute gradient has been analysed in a linearised framework by Anderson [28]. In a later work, the applicability of the linearised theory to this type of problem has been called into question by an experimental study by Nardi et al [27]. These authors measured the motion of lipid vesicles in a solute concentration gradient, and found a drift velocity more than 3 orders of magnitude faster than that predicted by the linearised theory, suggesting that a strong nonlinear coupling exists between osmosis and hydrodynamic flow. Our simulations do not include explicit solvent particles. Instead, we model the chucker as a diffusing hard sphere and the solute particles as diffusing hard spheres which interact only with the chucker. We use a dynamical Monte Carlo (MC) simulation scheme which has been shown to be equivalent to Brownian Dynamics for small trial displacements [22–25, 29]. By simulating a passive colloid in a fixed gradient of solute particles, we show that the naive kinetic result for the colloid velocity, expected for Brownian Dynamics simulations, is recovered in our MC simulations, at least for small solute particles. To estimate the likely effects of neglecting the detailed solvent-chucker interactions, we complement our MC simulations with a Langevin dynamics approach, in which the chucker is modelled by a diffusing point particle which experiences a drift force proportional to the local solute concentration gradient. The prefactor linking the force to the density gradient (which is proportional to λ ) can be varied, mimicking the effects that would be expected with explicit solvent. The Langevin simulations are in qualitative agreement with our MC results; this 4