25.9.0

nilbuild/developer-roadmap25.9.0Sep 17, 2025by sosahi

AI Summary

Adds support for new hardware (RTX Pro 6000, DGX B200) and advanced VLM capabilities, including custom vector database operators and Lambda stages.

Key Highlights

  • RTX Pro 6000 support
  • DGX B200 support
  • Custom vector database operator support
  • Custom Lambda stages support
  • Multimodal embedding documentation

New Features

  • RTX Pro 6000 functional support
  • DGX B200 functional support
  • nemoretriever-ocr-v1 support
  • llama-3.2-nemoretriever-1b-vlm-embed-v1 support
  • Llama Nemotron VLM 8b NIM support
  • Custom vector database implementation support
  • Custom Lambda stages support
  • Multimodal Embedding docs
  • Integer, float, boolean, and array metadata support in Milvus
  • Parallel VLM execution support

Full Release Notes

The NeMo Retriever extraction 25.09 release adds new hardware and software support, and other improvements, including the following:

- Add functional support for [RTX Pro 6000](https://www.nvidia.com/en-us/products/workstations/professional-desktop-gpus/rtx-pro-6000/).
- Add functional support for [DGX B200](https://www.nvidia.com/en-us/data-center/dgx-b200/).
- Add support for [nemoretriever-ocr-v1](https://build.nvidia.com/nvidia/nemoretriever-ocr-v1). For details, refer to [Deploy With Docker Compose (Self-Hosted)](https://docs.nvidia.com/nemo/retriever/latest/extraction/quickstart-guide/) and [NV-Ingest Helm Charts](https://github.com/nkmcalli/nv-ingest/tree/main/helm).
- Add support for [llama-3.2-nemoretriever-1b-vlm-embed-v1](https://build.nvidia.com/nvidia/llama-3_2-nemoretriever-1b-vlm-embed-v1).
- Add support for Llama Nemotron VLM 8b NIM for image captioning. For details, refer to [Extract Captions from Images](https://docs.nvidia.com/nemo/retriever/latest/extraction/nv-ingest-python-api/#extract-captions-from-images).
- Add support for custom vector database implementations. For details, refer to [Build a Custom Vector Database Operator](https://github.com/NVIDIA/nv-ingest/blob/main/examples/building_vdb_operator.ipynb).
- Add support for custom Lambda stages. For details, refer to [Add User-defined Stages to Your NeMo Retriever Extraction Pipeline](https://docs.nvidia.com/nemo/retriever/latest/extraction/user-defined-stages/).
- Expanded documentation for [Library Mode](https://docs.nvidia.com/nemo/retriever/latest/extraction/quickstart-library-mode/).
- New documentation [Configure Ray Logging](https://docs.nvidia.com/nemo/retriever/latest/extraction/ray-logging/).
- New documentation [Use Multimodal Embedding](https://docs.nvidia.com/nemo/retriever/latest/extraction/vlm-embed/).
- Add support for Integer, float, boolean, and array in custom metadata during Milvus entity creation.
- Add support for running more than one VLM at a time by using Helm. For details, refer to [NV-Ingest Helm Charts](https://github.com/nkmcalli/nv-ingest/tree/main/helm).

**Known Issues**

The following are the known issues for this release:

- A10G and L40S are not supported. For details, refer to [Support Matrix](https://docs.nvidia.com/nemo/retriever/latest/extraction/support-matrix/).
- `nemoretriever-parse` is not supported on RTX Pro 6000 or B200. For details, refer to [Support Matrix](https://docs.nvidia.com/nemo/retriever/latest/extraction/support-matrix/).
- The NeMo Retriever extraction pipeline does not support ingestion of batches that include individual files greater than approximately 400MB.