> This page is for OpenFold3, version 1.5.0.
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> - 1.6.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/openfold3/1.6.0/llms.txt
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> - 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

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## Release 1.1.0

### Summary

This release adds support for protein structural template inputs for complex structure prediction, and additional GPU hardware.

### New Features

#### Structural Template Support

The NIM now accepts protein structural template inputs (single-chain) to guide structure prediction:

* **Template input**: For each input, protein molecules can include structural templates in CIF format
* **Template guidance**: Templates help constrain and improve structure predictions when experimental or predicted structures are available
* **Multiple templates**: Each protein can have multiple structural templates

#### Additional GPU Support

Support for additional NVIDIA GPU configurations:

* **NVIDIA B200**: High-performance GPU for large-scale structure prediction
* **NVIDIA L40S**: Cost-effective GPU option for production deployments

#### Telemetry Control

**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.

**Benefits:**

* **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 only 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)

### Supported Features

All features from release 1.0.0 remain supported, with the addition of structural templates for protein molecules.