Choosing a model for GitLab Duo Self-Hosted
Picking a self-hosted model family for Code Suggestions, Chat and the Agent Platform from GitLab's support matrix, and what Full, Partial and Limited ratings mean for each feature.

Running GitLab Duo with self-hosted models and a self-hosted AI gateway inside your own infrastructure, including fully offline deployments.
Picking a self-hosted model family for Code Suggestions, Chat and the Agent Platform from GitLab's support matrix, and what Full, Partial and Limited ratings mean for each feature.
Planning GPU servers for self-hosted Duo models from GitLab's published examples: base system minimums, A100 and H200 counts by model size and capacity for concurrent developers.
Hosting Duo models on your own GPUs with vLLM behind an OpenAI-compatible endpoint, connecting it to the self-hosted AI gateway and operating it alongside GitLab.
Using AWS Bedrock or Azure OpenAI as the model platform for Duo Self-Hosted when private cloud is acceptable, and how it differs from on-premises GPUs for data residency.
Running Duo with no internet connectivity: offline licensing through the Agent Platform Self-Hosted add-on, self-hosted gateway and models, and features that the hybrid option would otherwise send outside.
Installing and running the self-hosted AI gateway that sits between GitLab and your models: placement, networking and version alignment with the GitLab instance.
Enabling the Duo Agent Platform, generally available on self-hosted deployments from GitLab 18.8, model support for agentic features and governance controls before rollout.
Which add-on a self-hosted Duo deployment needs: Duo Enterprise seats versus the Agent Platform Self-Hosted add-on for offline licenses, and usage-based billing for online licenses.

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