Air-gapped deployments can now run Mistral, GLM, Kimi, and MiniMax models on local inference hardware via vLLM, keeping code in-network while maintaining agentic capability.
Summary
Teams under data residency or compliance constraints no longer sacrifice AI capability—you can match model size to task complexity (routine work vs. complex reasoning) without sending code to third-party APIs. Eliminates the single-model bottleneck that previously forced isolated environments to choose between overkill or underpowered.
Why it matters
Teams under data residency or compliance constraints no longer sacrifice AI capability—you can match model size to task complexity (routine work vs. complex reasoning) without sending code to third-party APIs. Eliminates the single-model bottleneck that previously forced isolated environments to choose between overkill or underpowered.
Implementation verdict
Replaces cloud-dependent Duo Agent setups for regulated environments. Requires: vLLM serving platform, on-premises GPU hardware (or GPU VMs in VPC), and GitLab Duo Agent Platform Self-Hosted add-on. Ready now if you have infrastructure; hybrid deployments (mixing self-hosted + GitLab-managed models per feature) are supported. Contact sales to validate hardware requirements per model.
Sources
Dev Signal
Get briefs like this in your inbox — free, every weekday.
100+ sources compressed into one 4-minute read. Ranked, cited, implementation-ready.