Artificial Analysis
A broad view of model capability, with the evaluation recipe made explicit.
Independent sources. A clearer perspective.
Different tests answer different questions.
Find the evaluations that help you understand what a model can do.
An editorial guide, not a combined ranking. Scores from different methods are not directly comparable.
A broad view of model capability, with the evaluation recipe made explicit.
What people prefer when two answers are put side by side.
Release-based technical evaluation, with a newer long-horizon branch.
A view of AI performance grounded in particular kinds of professional work.
Can a system work out a new rule, rather than recognise a familiar answer?
Whether an agent can complete work through a real terminal environment.
Repository-level issues that require more than generating a short function.
Following policy, using tools and retrieving knowledge through a conversation.
Selecting tools and supplying the right arguments, across increasingly involved interactions.
How difficult a task can an agent complete, expressed in human task time?
A broad evaluation ecosystem whose different leaderboards need their own context.