Suiren-1.0 Technical Report: A Family of Molecular Foundation Models

• URL: http://arxiv.org/abs/2603.21942v1
• Date: Mon, 23 Mar 2026 12:59:43 GMT
• Title: Suiren-1.0 Technical Report: A Family of Molecular Foundation Models
• Abstract summary: Suiren-1.0 comprises three specialized variants (Suiren-Base, Suiren-Dimer, and Suiren-ConfAvg)<n>Suiren-1.0 establishes state-of-the-art results across a range of tasks.
• Score: 16.005665948017608
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising three specialized variants (Suiren-Base, Suiren-Dimer, and Suiren-ConfAvg) is integrated within an algorithmic framework that bridges the gap between 3D conformational geometry and 2D statistical ensemble spaces. We first pre-train Suiren-Base (1.8B parameters) on a 70M-sample Density Functional Theory dataset using spatial self-supervision and SE(3)-equivariant architectures, achieving robust performance in quantum property prediction. Suiren-Dimer extends this capability through continued pre-training on 13.5M intermolecular interaction samples. To enable efficient downstream application, we propose Conformation Compression Distillation (CCD), a diffusion-based framework that distills complex 3D structural representations into 2D conformation-averaged representations. This yields the lightweight Suiren-ConfAvg, which generates high-fidelity representations from SMILES or molecular graphs. Our extensive evaluations demonstrate that Suiren-1.0 establishes state-of-the-art results across a range of tasks. All models and benchmarks are open-sourced.

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