Abstract Understanding the mineralogy of exoplanets is essential for unraveling their interior structures, dynamics, and evolution. For large super‐Earths, the post‐post spinel Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$, one of the major mantle phases, may undergo the order‐disorder transition (ODT) at high temperatures. However, the ODT phase boundary of Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$ has not been rigorously constrained. Additionally, fundamental thermodynamic properties of the disordered Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$ remain poorly investigated. Here, we develop a unified machine learning potential (MLP) for Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$ of ab initio accuracy under super‐Earth mantle conditions. With the efficient MLP, we extensively calculate the free energy of post‐post spinel Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$ via the thermodynamic integration method. The results are used to constrain the ODT phase boundary. Furthermore, we report the P‐V‐T equation of state and Grüneisen parameters for post‐post spinel Mg2SiO4 ${\text{Mg}}{2}{\text{SiO}}{4}$ across various degrees of disorder. These thermodynamic properties are further applied to update the adiabatic thermal profiles and the mass‐radius relation of super‐Earths.

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