In this article
Choose an architecture from measured workload and owner conditions, not a universal ranking. RAM, VRAM and vCPU remain distinct resources.
An AI service can be hosted in several ways, moving costs and responsibilities between components. This helps GPU owners identify a role for their equipment and funders understand what an agreed budget creates. The following is an editorial architecture comparison, not a provider ranking or common benchmark.
Comparison criteria
We consider readiness, resource composition, data boundaries, updates and the unit of output. Price cannot be ranked without region, hardware and request profile. EC2 classification distinguishes compute, storage, memory-optimized and accelerated resources. Kubernetes GPU scheduling describes one device-management method, not a product-architecture decision.
System RAM, VRAM and vCPU remain different characteristics. No arrangement automatically replaces a shortage of one with the sum of the others.
Five arrangements to consider
| Arrangement | When to test | Main pilot question |
|---|---|---|
| CPU application and external model | Early task exploration | Complete answer and API conditions |
| One GPU server | A clear local setup | Combined resource load |
| Separate retrieval and GPU model | Distinct stage profiles | Networking and failure boundaries |
| Scheduled GPU batch | Work permits a timetable | Completing by the deadline |
| Startup on demand | Irregular requests | Cold start and readiness |
Qdrant capacity planning illustrates retrieval’s independent data-and-index budget. Cloud Run GPU is a particular managed capability whose conditions do not apply to all serverless offers.
Start with the smallest testable chain
Choose one task and define a correct result. For a document assistant, use questions with known relevant fragments and answer requirements. Test preparation, retrieval and model separately, then the full cycle. Infrastructure scaling does not resolve a product problem if a useful answer is still absent.
Preserve versions and data profiles. Comparing different models or documents can be useful research, but is not a clean comparison of hosting arrangements.
Test readiness and failure
A single server has fewer components, but maintenance may stop the entire chain. Separation adds interfaces and network dependencies. For batches, test restart after interruption. For on-demand startup, test the first post-idle request. For an external API, check request restrictions and unavailability handling.
One successful example does not demonstrate operational resilience. Every selected arrangement needs recovery conditions and responsible operators.
Resource roles in the architecture
A GPU, high-RAM server and operating funds can support different parts of the task. Identify the resource’s role before choosing attachment and budget.
Configurations are considered individually; ready-made implementations of all five arrangements are not announced. Prepare with CPU and GPU hosting, capacity planning and a technical pilot. Let measurement and owner conditions determine the choice.