25.9.0
ictnlp/LLaMA-Omni25.9.0Sep 17, 2025by sosahi
AI Summary
NeMo Retriever extraction 25.9.0 adds support for new high-end hardware (RTX Pro 6000, DGX B200) and new software components like nemoretriever-ocr-v1 and custom vector database implementations.
Key Highlights
- Functional support for RTX Pro 6000 and DGX B200
- Added support for nemoretriever-ocr-v1
- Added support for custom vector database implementations
- Added support for custom Lambda stages
New Features
- RTX Pro 6000 support
- DGX B200 support
- nemoretriever-ocr-v1 support
- llama-3.2-nemoretriever-1b-vlm-embed-v1 support
- Llama Nemotron VLM 8b NIM support
- Custom vector database implementations
- Custom Lambda stages
- Expanded documentation for Library Mode
- Multimodal embedding documentation
- Support for complex metadata types (Integer, float, boolean, array)
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.