> This page is for RFdiffusion, version 2.3.0 (Latest) (default).
> For other versions, use one of these documentation indexes:
> - 2.3.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/rfdiffusion/2.3.0/llms.txt
> - 2.2.0: https://docs.nvidia.com/nim/bionemo/rfdiffusion/2.2.0/llms.txt
> - 2.0.0: https://docs.nvidia.com/nim/bionemo/rfdiffusion/2.0.0/llms.txt
> - 1.0.0: https://docs.nvidia.com/nim/bionemo/rfdiffusion/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 Notes

## April 3, 2026

## Release 2.3.0

### Summary

* **GB200 support**: NVIDIA NIM for RFdiffusion now supports NVIDIA GB200 (Grace Blackwell) for improved inference performance and scalability.

* **NIMTools 1.6.1**: Updated to NIMTools 1.6.1.

* **Telemetry control**: NIM Telemetry helps NVIDIA deliver a faster, more reliable experience with greater compatibility across a wide range of environments, while maintaining strict privacy protections and giving users full control.

### Key Features

* **Enhances performance and reliability**: Provides anonymous system and NIM-level insights that help NVIDIA identify bottlenecks, tune performance across hardware configurations, and improve runtime stability.

* **Improves compatibility across deployments**: Helps detect and resolve version, driver, and environment compatibility issues early, reducing friction across diverse infrastructure setups.

* **Accelerates troubleshooting and bug resolution**: Allows NVIDIA to diagnose errors and regressions faster, leading to quicker support response times and higher overall availability.

* **Informs smarter optimizations and future releases**: Real-world, aggregated telemetry data helps guide the optimization of NIM runtimes, model packaging, and deployment workflows, ensuring updates target the scenarios that matter most to users.

* **Protects user privacy and data security**: Collects minimal, anonymous metadata, such as hardware type and NIM version. No user data, input sequences, or prediction results are collected.

* **Fully optional and configurable**: Telemetry collection is disabled by default. You can toggle telemetry at any time using environment variables.

**Configuration:**

* Set `NIM_TELEMETRY_MODE=0` to disable telemetry (default)
* Set `NIM_TELEMETRY_MODE=1` to enable telemetry

For more information about data privacy, what is collected, and how to configure telemetry, refer to:

* [NVIDIA's Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/)
* [NIM Telemetry Settings](https://developer.nvidia.com/docs/nim-tools/latest/templates/nimlib/nim-telemetry.html)

## May 22, 2025

## Release 2.2.0

### Summary

This release brings improved performance and stability through the following system updates:

* Enhanced system stability and performance with our latest core system updates
* Improved integration with our advanced protein design platform for better results