Frederick Jensen shared an interesting benchmark on LinkedIn, comparing 63 AI-generated Power BI reports across 7 models and 3 reasoning effort levels. Here are the key findings: Best cost efficiency: GPT SOL 6.1 (Low effort) generated a production-ready report for just $1.51 in 9 minutes , outperforming comparable Claude models on cost. Fastest model: Claude Opus 5.5 (Low effort) completed the same task in just 7 minutes , but cost $4.49 . Quality: Most models fully met the requirements. Only the smaller Claude Haiku and OpenAI Luna models failed to do so. The report included interactive slicers, a map with custom tooltips, bookmarks, dynamic charts, conditional formatting, and KPI cards with SVG visuals. The benchmark used the same prompt three times for every model/effort combination, with each report individually reviewed and scored. The takeaway? AI can already build sophisticated Power BI reports, but choosing the right model and effort level can make a significant difference in cost and execution time. Source and credit: Frederick Jensen (LinkedIn) submitted by /u/m3nt3_
Originally posted by u/m3nt3_ on r/ArtificialInteligence