Frequently asked questions
How can AI model performance and cost be compared?
Compare benchmark scores and measured task costs within the same evaluation version, while checking each model’s reasoning settings. Input/output prices alone do not measure performance. Missing measurements are left unknown.
Is the highest-scoring model always best for me?
No. Benchmark scores describe a specific evaluation. Your task, latency, reasoning settings and total cost can change the choice. Use the score and cost columns together, and open the benchmark source for its conditions.
Does an unknown benchmark score mean a model performs badly?
No. It means a comparable verified measurement is unavailable in this catalog. We do not assign zero or estimate a score from a model name or token price. Missing values remain separate from measured results.