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After evaluating Suprmind, Claude Pro, and Perplexity Pro, we’re canceling Claude and Perplexity to streamline workflows

When different models disagree on a prediction, it often signals tricky or risky inputs worth a closer look. Tracking ensemble variance or margin helps identify these cases

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Model disagreement helps spot risky inputs by measuring uncertainty with metrics like entropy or ensemble variance. When models strongly disagree, those cases often need extra attention

When AI models disagree, it’s not a flaw but a feature that can expose hidden errors and reduce silent hallucinations

OpenRouter acts as a simple model aggregator, letting you switch between models easily but each call resets the context, so it’s not great for workflows that rely on keeping info flowing