TensorNet-PES-MatPES-PBE-2025.2-m

Introduction

Pre-trained TensorNet foundation potential, i.e., universal machine learning interatomic potential trained on the MatPES-PBE-2025.2 dataset. This is a medium-size TensorNet variant (~1.07M parameters; units=128, nblocks=3), one block deeper than the standard materialyze/TensorNet-PES-MatPES-PBE-2025.2 reference (0.84M).

Potential

matgl Potential model (version 3).

Usage

import matgl

model = matgl.load_model("materialyze/TensorNet-PES-MatPES-PBE-2025.2-m")

Model Details

• Number of parameters: 1,067,906

Metrics

Split	Energy MAE (eV/atom)	Force MAE (eV/A)	Stress MAE (GPa)
Train	0.037036	0.111566	0.440905
Validation	0.037056	0.130899	0.592677
Test	0.037167	0.125499	0.592749

Metadata

{
  "dataset": "MatPES-PBE-2025.2",
}