Sup AI
Confidence-weighted AI ensemble that topped Humanity's Last Exam
Expert verdict
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2-1The Panel's Take
Sup AI uses a confidence-weighted ensemble of multiple AI models to answer hard questions. Each model rates its own confidence, and the system aggregates responses weighted by that confidence. Achieved 52.15% on Humanity's Last Exam benchmark, outperforming individual models.
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Sup AI verdict: SHIP 🚀 2 ships · 1 skip from the expert panel Full review: shiporskip.io/tool/sup-ai
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<a href="https://shiporskip.io/api/badge-click/sup-ai" target="_blank" rel="noopener"><img src="https://shiporskip.io/api/badge/sup-ai" alt="Sup AI Ship verdict on ShipOrSkip" width="360" height="90" /></a>[](https://shiporskip.io/api/badge-click/sup-ai)<iframe src="https://shiporskip.io/embed/sup-ai" title="Sup AI ShipOrSkip verdict" width="360" height="260" style="border:0;border-radius:16px;max-width:100%;" loading="lazy"></iframe>The reviews
“Confidence-weighted ensembling is the quiet breakthrough everyone is sleeping on. Individual models plateau — but smart aggregation keeps pushing the frontier. Sup AI scoring 52% on Humanity's Last Exam when no single model breaks 40% proves the thesis.”
“The benchmark result is legitimately impressive and the methodology is transparent. My concern is latency — querying multiple models and aggregating adds significant time. For research and high-stakes questions it is worth the wait. For everyday chat it is overkill.”
“No API, no self-hosting option, and the ensemble approach means your per-query cost is 3-5x a single model call. The benchmark numbers are compelling but I cannot integrate this into a product. Ship an API and I will reconsider.”