
Daniel Orson builds practical AI tools and writes about model selection, benchmark context, cost, and agent workflows at Dervity.
His research draws on provider documentation, Artificial Analysis data, Arena results, practitioner reports, and selected hands-on tests. Sourced numbers and his own observations are kept separate, so you can see where each recommendation comes from.