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Six architectures that should not be confused

Reviewed September 7, 2026 · Independent educational resource

The following comparison describes engineering patterns. It does not certify compatibility or predict performance for a particular combination of hardware and software.

PatternWhat changesWhat remains to prove
One inference workstationOne machine runs the model and serves clients.Model fit, sustained load, service configuration and recovery.
Request routingAn endpoint chooses among separate inference servers.Backend eligibility, model equivalence, authentication, queue policy and routing overhead.
Workload schedulingJobs are assigned to available machines.Job isolation, resource accounting, placement and whether tasks can run independently.
Distributed model executionOne inference computation spans supported devices or nodes.Runtime support, interconnect, model partitioning, memory overhead and failure handling.
Highly available inferenceA service is designed to continue through component failures.Redundant coordination, health checks, model availability, retries and tested recovery.
Devices on one networkMachines can potentially communicate.Every inference service, authentication, routing and resource-management layer still needs configuration.

An example request-routing path

An application sends a request to a local endpoint. The router selects a node that has the intended model and enough available capacity. That node executes its own inference and returns a response. Different requests may go elsewhere. If the request requires a feature absent from another backend, an apparently healthy spare node may still be ineligible.

An example distributed-execution path

A distributed runtime places different parts of the model or computation on supported devices. Nodes exchange intermediate information while producing one response. Communication overhead can dominate a slow interconnect. Failure of a participating node can interrupt that response. The exact behavior depends on the implementation, not the number of networked machines.

A useful acceptance test

Write down the model, quantization, context, concurrency and task quality requirement. Measure one-node behavior first, then the proposed topology using the same inputs. Capture total completion time, error rate, queue delay, power and recovery. Keep the raw test conditions with the results. No benchmark values are supplied here because this site has not measured your hardware.

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