You must choose among models. What is the most reliable basis?
Why A is the answer
Benchmarks on your own task, against cost and latency targets
Benchmarks on your own task, against cost and latency targets, show which model fits your use case.
In detail
- Test on your own task against your cost and latency targets.
- Public rankings may not reflect your task.
Use case
An illustrative scenario, not a real incident.
A team tests three models on real tickets against cost and latency targets, and a mid-priced model wins.
See it in different ways
flowchart LR
A["Business need"] --> B["Proof of concept"]
B --> C{"Feasible and valuable?"}
C -->|Yes| D["Production design"]
C -->|No| E["Change the approach or stop"]sequenceDiagram participant S as Service participant L as Abstraction layer participant C as Configuration participant M as Model S->>L: Request L->>C: Which model? C-->>L: Model ID L->>M: Call M-->>S: Response
flowchart LR S0["Real tasks"] --> S1["Run candidates"] --> S2["Measure quality, cost and latency"] --> S3["Choose"]
Key point: Benchmark on your own task.
Why the other options are wrong
- B. The newest release, because new models are better at every task
- New does not mean better for every task.
- C. The longest context window, because longer is better for all prompts
- Long windows are not always useful.
- D. The most expensive model, because a higher price means better results
- Price does not prove fit.