What Is Benchmark Grade?
ModelPicker's rating system for LLMs. Models are scored 1-3 on 12 real-world tasks and graded as Weak, Usable, or Strong.
We test every model on 12 practical tasks that developers actually use LLMs for: generating JSON, calling tools, compressing text, maintaining a persona, and more. Each task is scored 1-3 by an LLM judge. The average across all tasks determines the overall grade.
Strong (2.4-3.0/3) means the model produces output you could hand to a stakeholder without editing. Usable (1.7-2.3/3) means it follows instructions and produces reasonable output but needs human review. Weak (1.0-1.6/3) means it failed to follow instructions or produced unusable output.
Our benchmarks differ from academic benchmarks like MMLU or HumanEval because we test real developer workflows, not academic knowledge. A model that scores poorly on MMLU might score Strong on our structured output test if it follows JSON schemas reliably.