Benchmarking the Model Is the Wrong Abstraction

Benchmarking the workflow is the right one. I've spent over a year benchmarking AI models. Thousands of evaluations across 100+ models, dozens of task types, multiple scoring modes. And the single biggest thing I've learned is something most people in this space haven't internalized yet: Model performance is not a number. It's a function. performance = f( model, task_type, task_theme, prompt_structure, output_constraints, decoding_parameters, dataset_distribution ) Change any one of these variables, and the rankings reshuffle. Sometimes dramatically.