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DeePMD-kit
A deep learning package for many-body potential energy representation and molecular dynamics, designed to minimize the effort required to build deep learning-based models of int...
What is DeePMD-kit?
A deep learning package for many-body potential energy representation and molecular dynamics, designed to minimize the effort required to build deep learning-based models of interatomic potential energy and force fields and to perform MD. Interfaced with TensorFlow, PyTorch, JAX, and Paddle backends, and with LAMMPS, i-PI, AMBER, CP2K, GROMACS, OpenMM, and ABACUS.
Product typeScientific Models
Pricing ·
Deployment
APINot available
What teams use DeePMD-kit for
Building deep learning-based models of interatomic potential energy and force fields
Performing molecular dynamics (MD)
Simulating finite molecules, extended systems, metallic systems, and chemically bonded systems
Integrations and access
Platforms, integrations, and language support vary by plan and region. Confirm final requirements with the vendor.
Platforms
IntegrationsAPI and webhooks
Languages
Support
What reviewers say
Community reviewsReviews are owned and editable by their authors.
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Enterprise readiness
Compliance claims are normalized from current vendor documentation and independently reviewed by SOTA2.
Data retention:
Benchmarks and comparisons
Independent benchmarksStructured task results are being verified.
Side-by-side comparisonsComparison workspaces will be available in a later release.
