AI model selection paralysis when solving computationally complex problems

Developers and researchers struggle to determine which AI model (Fable 5 vs GPT-5.6 Sol) actually solves their specific NP-Hard computational problems effectively, wasting time on trial-and-error testing instead of shipping solutions. Current AI benchmarking tools provide generic performance metrics but fail to answer the critical question: 'Will THIS model solve MY specific hard problem?' This forces teams to manually test multiple expensive models, delaying project timelines and inflating infrastructure costs.