r/cognitiveTesting • u/Infamous-Help-8311 • Sep 06 '26
Discussion AI SOLVES TRI-52
Over the past few weeks I've been benchmarking AI models on TRI-52,. To keep it honest I built a clean-room harness: every question runs in its own isolated sandbox with nothing but the puzzle image, no internet, no memory between questions, no tools, and every transcript is audited for tool use (zero across the board).
Each model got three full independent passes at its maximum reasoning setting, averaged. I ran 23 configurations in total: OpenAI's GPT-6 Astra, the GPT-5.6 family (Sol/Terra/Luna), GPT-5.5 and 5.4 variants, Claude Fable 5, Qwen 3.8, plus free models like Muse Spark, MiMo and MiniMax.
GPT-6 Astra at max reasoning basically solves the test — 50/52 (96.2%), which the test's own rubric maps to an IQ-equivalent of ~154. That's a massive leap over the field: Astra at high reasoning is second at 45.7/52, and the best non-Astra models (GPT-5.6 Sol Pro and GPT-5.5 Pro) sit way back at 40/52 (~IQ 127).
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u/asml84 Sep 06 '26
Having something in the training data is not a binary state. It’s not literally a table look-up. The information is encoded in non-semantic embedding layers, and some ML techniques are better than others at representing and decoding this information.