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Release Notes#

Release 1.0.0#

Summary#

This is the first release of NVIDIA NIM for Batched Geometry Relaxation.

Features#

The 1.0.0 release includes the following key features:

  • Multiple MLIP Models: Support for MACE, AIMNet2 (with NSE variant), and TensorNet models.

  • Dynamic Batching: Automatic batch size estimation optimized for available GPU memory.

  • GPU-accelerated FIRE2 Optimizer: High-performance geometry optimization directly on GPU.

  • Cell Optimization: Optional unit cell optimization with pressure tolerance constraints.

  • DFT-D3 Dispersion: Optional DFT-D3(BJ) dispersion corrections for improved van der Waals interactions.

  • Per-request Parameters: Override global optimization parameters on a per-request basis.

  • Active Masks: Freeze specific atoms during optimization.

Limitations#

The following limitations apply to the 1.0.0 release:

  • External model weights: You must provide AIMNet2 and TensorNet models externally by using a volume mount. Only MACE is downloaded automatically. For instructions, refer to Custom Models.

  • Fixed PBC mode: Periodic boundary conditions (PBC) mode is fixed at container startup. You cannot mix periodic and non-periodic structures in the same container instance.

  • Memory constraints: Very large structures can exceed GPU memory limits and result in an out-of-memory HTTP error. Use the /v1/status endpoint to check the max_system_size (maximum number of atoms per system) for your configuration.

Example: Checking the Maximum System Size

To view the constraints for your deployment, query the /v1/status endpoint:

curl -X GET http://localhost:8000/v1/status

For more details, refer to the API Reference.