> This page is for GenMol, version 2.0.0 (Latest) (default).
> For other versions, use one of these documentation indexes:
> - 2.0.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/genmol/2.0.0/llms.txt
> - 1.0.1: https://docs.nvidia.com/nim/bionemo/genmol/1.0.1/llms.txt
> - 1.0.0: https://docs.nvidia.com/nim/bionemo/genmol/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 24, 2026

## Release 2.0.0

### Summary

This release upgrades GenMol to the `NV-GenMol-89M-v2` checkpoint and updates the NIM documentation, validation matrix, and API contract for the v2 service.

### Model and Platform Updates

* Updated the GenMol NIM to version `2.0.0`
* Integrated the `NV-GenMol-89M-v2` checkpoint
* Validated GPU matrix expanded to 13 SKUs:
  * Ampere: A10G, A100
  * Ada Lovelace: L40S, RTX6000 Ada
  * Hopper: H100, H200
  * Blackwell: B200, B300, RTX6000 Blackwell
  * Grace Hopper: GH200
  * Grace Blackwell: GB200, GB300
  * DGX Spark: GB10

### Generation Quality

* Motif-extension wall-time on H100 improved from 1.82s in v1 to 1.051s in v2 — a reduction of approximately 42%, at comparable scaffold-decoration latency
* Scaffold-decoration validity on H100 improved from 0.967 in v1 to 0.995 in v2
* Higher output diversity on fragment-completion tasks
* Substantially improved success rate on one-step linker design, a v2 capability where v1's success rate was prohibitively low

For the full per-metric H100 v1 vs v2 comparison (wall-time and accuracy across both
benchmark tasks), refer to the [Benchmarks](/nim/bionemo/genmol/benchmarks) page.

### API and Runtime Updates

* `temperature` default remains `1.0`
* `noise` default is `1.0` with supported range `0.0-2.0`
* `step_size` is deprecated in v2 and is accepted only for backward compatibility
* Startup guidance now includes persistent cache mounting for model artifacts

### Bug Fixes

* Fixed incorrect version metadata responses for the v2 service
* Fixed plain SMILES request handling
* Fixed under-delivery when invalid generations were filtered out
* Improved uniqueness behavior for generated molecules
* Improved fragment preservation for guided generation
* Mitigated recursion-depth failures under concurrent sustained load by serializing access to the shared in-process model instance

### 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 with anonymous system and NIM-level insights that help identify bottlenecks, tune performance across hardware configurations, and improve runtime stability
* Improves compatibility across deployments by helping detect and resolve version, driver, and environment compatibility issues earlier
* Accelerates troubleshooting and bug resolution, enabling faster diagnosis of errors and regressions
* Informs future optimizations and releases using aggregated real-world deployment insights
* Protects user privacy by collecting minimal, anonymous metadata (for example, hardware type and NIM version); user prompts and generated molecule outputs are not collected
* Is fully optional and configurable; telemetry collection is disabled by default

**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 telemetry configuration, 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)

## August 27, 2025

## Release 1.0.1

### Summary

This release includes security updates and CVE fixes to improve the overall security posture of the NIM.

### Security Updates

* Fixed multiple Common Vulnerabilities and Exposures (CVE) issues in dependencies
* Updated container base images to address known security vulnerabilities
* Enhanced security scanning and validation processes

### Bug Fixes

* Resolved potential security vulnerabilities in third-party dependencies
* Improved error handling for edge cases

## January 2, 2025

## Release 1.0.0

### Summary

This is the first general release of NIM.

### Limitation

* GenMol NIM uses only one GPU device. If multiple devices are visible to the NIM container, only the first one will be used.