The gradient discretisation method is a generic framework that is applicable to a number of schemes for diffusion equations, and provides in particular generic error estimates in L 2 and H 1 -like norms. In this paper, we establish an improved L 2 error estimate for gradient schemes. This estimate is applied to a family of gradient schemes, namely, the Hybrid Mimetic Mixed (HMM) schemes, and yields an O(h 2 ) super-convergence rate in L 2 norm, provided local compensations occur between the cell points used to define the scheme and the centers of mass of the cells. To establish this result, a modified HMM method is designed by just changing the quadrature of the source term; this modified HMM enjoys a super-convergence result even on meshes without local compensations. Finally, the link between HMM and Two-Point Flux Approximation (TPFA) finite volume schemes is exploited to partially answer a long-standing conjecture on the super-convergence of TPFA schemes.Proof. The proof hinges on two tricks. In Step 1, letting u D * be the solution to the modified HMM scheme, we show thatCombined with the result from Step 1 and the super-convergence property (4.8) of the modified HMM method, this concludes the proof.Step 1: Comparison of the solutions to the schemes for D and D * . Let u D * be the solution to (2.1) with D * instead of D. Subtracting the two gradient schemes corresponding to D * and D we see that, for all v D ∈ X D,0 , Ω