> This page is for OpenFold3, version 1.6.0 (Latest) (default).
> For other versions, use one of these documentation indexes:
> - 1.6.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/openfold3/1.6.0/llms.txt
> - 1.5.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.5.0/llms.txt
> - 1.4.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.4.0/llms.txt
> - 1.3.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.3.0/llms.txt
> - 1.2.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.2.0/llms.txt
> - 1.1.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.1.0/llms.txt
> - 1.0.0: https://docs.nvidia.com/nim/bionemo/openfold3/1.0.0/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nim/bionemo/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nim/bionemo/_mcp/server.

## Release 1.2.0

### Summary

This release adds support for GB200 GPU with ARM architecture and extends hardware compatibility for enterprise deployments.

### Key Features

* **GB200 Support**: Added support for GB200 GPU
* Enhanced compatibility with ARM-based systems

### Notes and Limitations

* Ensure you use this NIM with GPUs with at least 48 GB of VRAM.
* **CUDA Driver Requirements**:
  * Minimum version 580 with CUDA 13.0
* **TensorRT Engine Speedup**: To achieve optimal prediction speedup using TRT engines, this version uses TensorRT 10.11.0. Refer to the [TensorRT 10.11.0 Support Matrix](https://docs.nvidia.com/deeplearning/tensorrt/10.11.0/getting-started/support-matrix.html) to ensure your CUDA Driver and CUDA Toolkit versions are compatible.

> **Note**
>
> While there are many options for tuning this NIM's performance, for most users, the defaults will provide a balanced performance experience.