AI hosting decision center
Managed hosting, VPS, dedicated hardware and GPU cloud solve different problems. Start with where the model runs, what must stay online and how much infrastructure you want to operate.
Free decision tools. No universal hosting winner or invented provider rankings.
Choose your starting point
Each guide explains when an option fits and what you still need to verify.
Managed hosting
Compare managed platforms and deployment services when you want to spend more time on the agent and less on server upkeep.
What to verify: Check runtime limits, data portability, background jobs and restart behavior.
Explore managed hosting →CPU VPS
A VPS is a flexible starting point when the agent calls a hosted model API and needs its own queues, storage and scheduled tasks.
What to verify: You own OS patching, access control, monitoring, backups and recovery.
Plan VPS requirements →Dedicated server
Compare dedicated infrastructure when isolation, predictable capacity and hardware control justify an ongoing commitment.
What to verify: Account for hardware, utilization, provisioning and operating effort.
Compare dedicated servers →Self-hosted runtime
Compare self-hosted agent approaches by deployment complexity, security boundaries, persistence and day-two operations.
What to verify: Local and self-managed systems still need safe remote access and recovery.
Explore self-hosted agents →Compare by workload
A lightweight agent calling an external AI API does not automatically require a GPU. GPU compute matters when the infrastructure also runs inference or other GPU-heavy work.
| Hosting model | Useful when you need | Verify before committing |
|---|---|---|
| Managed platform → | Simpler deployment and less direct OS management | Background services, constraints, state export and billing |
| CPU VPS → | Always-on orchestration using remote model APIs | RAM for browsers/workers, restarts, access and backup |
| Dedicated server → | Reserved resources and isolation for sustained work | Utilization, hardware configuration and operating cost |
| GPU cloud → | Model inference that needs rented GPU compute | VRAM, GPU hours, storage, network egress and idle time |
| Local hardware → | On-premise processing or access to local devices and data | Power, connectivity, capacity, security and remote recovery |
This is a decision framework, not a live price table or a benchmark. Check current provider specifications.
A hosting decision also needs persistent state, monitoring, recovery and a documented budget. Use the free reliability guide or carry the full decision into the $19 Recommendation Kit.