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I gave seven AI models the same twelve-instruction account research prompt and manually verified every disputed claim. Perplexity completed 10 of 12 instructions. Gemini completed 1. The gap between the best and worst model was 5 points on a 10-point scale. In this video: The full rankings, Perplexity, GPT 5.2, Grok 4.2, Grok 4, Claude Opus 4.6, Claygent, Gemini 3 Pro Why I went from 3 scoring criteria to 6 weighted categories (accuracy, business relevance, web access, reasoning, completeness, research usability) Zero hallucinations across all 7 models — but 3 false claims that could send your SDR to the wrong person The one model that found a VP of SDR, a $400M funding round, and a $1B revenue target that 6 other models missed Why 49% of all misses were search strategy failures — models didn't think to look, not that they couldn't My decision framework: Perplexity or GPT for research, Claude for analysis, Gemini for writing Web app vs Clay: every score in this test is the ceiling, not the floor Referenced: TrackRec: https://www.trackrec.co Replit: https://replit.com Perplexity: https://www.perplexity.ai Clay: https://www.clay.com RepVue: https://www.repvue.com The account research prompt: Available for Outbound Kitchen paid members Chapters: 0:00 - Why I keep benchmarking AI models 1:45 - The test setup: TrackRec researching Replit 3:00 - What changed from v1 (6 criteria, instruction tracking) 3:30 - The new rankings 4:05 - Perplexity: VP of SDR, podcast, RepVue miss 5:00 - GPT 5.2: zero false claims, Glassdoor depth 5:30 - The $400M funding round — is it real? 7:00 - Grok 4.2: 56 seconds, best RepVue data 8:00 - Bottom four models (quick summary) 8:55 - Verification: hallucinations vs false claims 10:05 - Which models I recommend 10:45 - Web app vs Clay availability 11:30 - What's next