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Release Notes

December 2, 2025

Release 1.4.0

Summary

This release addresses security vulnerabilities, integrates the latest cuEquivariance library, and introduces new features including telemetry control and confidence score persistence capabilities.

Key Features

  • Security: Addressed all CVE (Common Vulnerabilities and Exposures) issues

  • cuEquivariance integration: Updated to cuEquivariance 0.7.0 for improved equivariant operations

  • Enhanced B200 support: Enabled trimul kernel optimization for B200 SKUs in PyTorch backend

  • Extended sequence length: Support for longer sequences up to 2048 residues on A100, H100, and B200 GPUs with TensorRT-BioNeMo

  • Confidence score persistence: Implemented Docker volume mounting flag to expose output directories with per-sample confidence scores, enabling result persistence in NIM cache folder. Configure using:

    • Set NIM_EXPOSE_CONFIDENCE_SCORES=true to enable confidence score output
    • Set NIM_EXPOSE_CONFIDENCE_SCORES=false to disable (default)

  • 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: