Compare on the task.
Test candidate models against your own examples. Include difficult cases, cost per completed task and response time.
Model orchestration
The model is a component.Keep the architecture yours.
Choose models around quality, latency, cost and data restrictions. Make routing and fallback deliberate, testable decisions.
Explore the capabilityENGINEERING FOCUS
01Classify the request
02Apply permitted route
03Evaluate the result
One model need not do every job.
Some workloads benefit from specialised routes; others are simpler with one model. Evaluate representative tasks before adding an orchestration layer.
Control the context.
Manage prompts, structured output and context budgets. Version the settings that affect behaviour.
Plan the fallback.
Restrict allowed providers and regions. A failure should not reroute sensitive information to an unapproved destination.
A possible workflowIllustrative example.
Use an approved model for a sensitive workflow and stop, rather than widen the data boundary, if it is unavailable.
Provider abstraction does not make models interchangeable. Run evaluations before changing a model or route.
A closer look
Good questions.
Straight answers.
Can we avoid dependence on one provider?
Designing clear interfaces can reduce unnecessary coupling. Provider features, terms and model behaviour still differ.
Is the cheapest model the most economical?
Not always. Retries, failures, review effort and task completion all affect the actual operating cost.
Technical reference: Anthropic: evaluating AI agents (opens in a new tab)
Keep exploring