Self-hosted artificial intelligence means deploying model weights and serving software on hardware an organization controls. The infrastructure may be a local workstation, private data center or chosen cloud account rather than a hosted model API operated by the original provider.
Self-hosting can improve deployment control, data governance and provider independence, especially when open weights are available. It also transfers responsibility for hardware, security, updates, monitoring and performance optimization to the operator, so it is not automatically cheaper or simpler.
Acronyms and aliases
local AI deployment synonymself-hosted AI variant
Specialised terms
Related terms
Frequently asked questions
Why do organizations self-host AI models?
Common reasons include data control, predictable deployment, customization, offline operation and less dependence on one API provider. The value depends on workload and operational capacity.
Is self-hosted AI always less expensive?
No. It avoids some provider charges but introduces hardware, energy, engineering and maintenance costs. High utilization can improve economics, while occasional workloads may be cheaper through an API.
