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Release Notes for NVIDIA NeMo Retriever Embedding NIM#

This documentation contains the release notes for NVIDIA NeMo Retriever Embedding NIM.

Note

Some releases are labelled “Production Branch” or “(PB)”. Production Branches provide reliable, stable versions of the NIM. Non-production branch releases (sometimes called Feature Branch (FB) releases) contain the latest features, improvements, and optimizations.

Release 2.3#

This release adds support for NVIDIA DGX Spark to the nvidia/llama-nemotron-embed-vl-1b-v2 NIM.

Highlights#

  • Added FP16 and FP8 support for NVIDIA GB10 on DGX Spark.

  • Added aarch64/Arm64 container support for DGX Spark deployments.

  • The standard single-GPU Docker deployment workflow now supports DGX Spark. For details, refer to Get Started.

  • Removed NVIDIA RTX PRO 6000 Blackwell Workstation Edition from the claimed support set. NVIDIA RTX PRO 6000 Blackwell Server Edition remains supported.

For details, refer to Support Matrix.

All Known Issues#

The known issues for NeMo Retriever Embedding NIM are the following:

  • The container health check used by Docker and Docker Compose can report the container as unhealthy even when the NIM is ready. This can block Compose dependencies that require service_healthy.

    Workaround: Override the health check in Docker Compose:

    healthcheck:
  test: ["CMD", "/usr/bin/curl", "-fsS", "http://127.0.0.1:8000/v1/health/ready"]

  • For nvidia/nemotron-3-embed-1b, setting NIM_SERVER_MAX_QUEUE_SIZE=0 can cause the NIM to log an error during padded-batcher startup instead of rejecting the invalid configuration. Use the default value, 1024, or set NIM_SERVER_MAX_QUEUE_SIZE to a positive integer.

Release Notes for Previous Versions#