Provision of Canadian Large Language Model (LLM) for Inference

Objective of this project is to run additional Large Language Models locally in our

existing infrastructure within the National Research Council Canada’s Azure Cloud. The

Large Language Model should provide an API with a means to be queried against, and

an appropriate response returned. There should be no data exfiltration, with all

computation occurring locally. For data sovereignty and security, the provider of the

LLM should primarily operate within Canada. The provided LLM is expected to be

general use and meeting common industry benchmark metrics (MMLU, GPQA, IFEval,

ChatRAGBench, StrategyQA, and others) within 5 percentage points or better of

previous or current generation industry models (GPT-4o, Llama 3.3 70B, Mistral Large

2, DeepSeek V3, Gemini 2.0 Pro, etc.). The model should also be built and trained by

the vendor from the ground up, without relying on tuning or re-training any existing

models. The provider will be engaged for licensing and installation assistance.

The NRC is exploring the deployment of Large Language Models (LLMs) within its

secure cloud computing environment, seeking to operate LLMs locally and ensure that

all data processing and computation occur entirely within the controlled environment,

maintaining strict data sovereignty and security standards.

Preliminary technical work has been completed to establish the foundation for this

undertaking, including the setup of a GPU-based virtual machine that is able to

communicate with the in-house developed LLM service delivery platform.

This initiative aligns with NRC’s ongoing commitment to advancing secure, sovereign AI

capabilities that support Canadian innovation, protect sensitive information, and ensure

compliance with government data management standards.

A contracting officer can use limited tendering for specific reasons outlined in the applicable trade agreements. The reason for this contract is described below:

• None