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Support Matrix for NeMo Retriever Extraction

Before you begin using NeMo Retriever extraction, ensure that you have the hardware for your use case.

Core and Advanced Pipeline Features

The Nemo Retriever extraction core pipeline features run on a single A10G or better GPU. The core pipeline features include the following:

  • llama3.2-nv-embedqa-1b-v2 — Embedding model for converting text chunks into vectors.
  • nemoretriever-page-elements-v2 — Detects and classifies images on a page as a table, chart or infographic.
  • nemoretriever-table-structure-v1 — Detects rows, columns, and cells within a table to preserve table structure and convert to Markdown format.
  • nemoretriever-graphic-elements-v1 — Detects graphic elements within chart images such as titles, legends, axes, and numerical values.
  • paddleocr — Image OCR model to detect and extract text from images.
  • retrieval — Enables embedding and indexing into Milvus.

Advanced features require additional GPU support and disk space. This includes the following:

Hardware Requirements

The following are the hardware requirements to run NeMo Retriever Extraction.

GPU Option H100 A100 A10G L40S
Family SXM or PCIe SXM or PCIe
Memory 80GB 80GB 24GB 48GB
Core Features Total GPUs 1 1 1 1
Core Features Total Disk Space ~150GB ~150GB ~150GB ~150GB
Audio Additional Dedicated GPUs 1 1 1 1
Audio Additional Disk Space ~37GB ~37GB ~37GB ~37GB
nemoretriever-parse Additional Dedicated GPUs 1 1 1 1
nemoretriever-parse Additional Disk Space ~16GB ~16GB ~16GB ~16GB
VLM Additional Dedicated GPUs 1 1 1 1
VLM Additional Disk Space ~16GB ~16GB ~16GB ~16GB