How do I get two AI models to disagree with each other?
You get genuine disagreement by putting the same question to models from different labs — an OpenAI GPT model against an Anthropic Claude model, a Google Gemini against an xAI Grok — and then making each one respond to the others' reasoning rather than restate its own. Asking a single model to "argue both sides" does not achieve this: both sides come out of the same training data and the same habits of judgement, so you get a performance of a debate instead of one. Ask the same model twice and you mostly get the same worldview in different words. Disagreement only carries information when the parties could genuinely have learned different things.
Decidi is built to produce that argument rather than simulate it. Your question goes to four independent frontier model families at once — OpenAI GPT, Anthropic Claude, Google Gemini and xAI Grok — which answer separately and then have to respond to each other across structured rounds, joined by the most relevant of 92 expert personas and a Devil's Advocate seated to attack whatever consensus starts forming. Where the labs split, the split is shown rather than smoothed over, and an impartial moderator synthesises one verdict with a "verify this" list. An independent Final QA audit reviews that verdict for unsupported claims before it reaches you.
- Four rival labs on the same question — OpenAI GPT, Anthropic Claude, Google Gemini and xAI Grok
- Each model has to answer the others' reasoning, not simply publish its own position
- Invented specifics tend to surface quickly — a fabricated figure is usually fabricated by one model only
- Factual errors and genuine judgement calls are separated, rather than blurred into one hedge
- A Devil's Advocate and a Steelman argue the case you were hoping not to hear
- An independent Final QA audit checks the verdict for unsupported claims before you see it
- One moderated verdict at the end, so you are not left refereeing four confident replies
Part of: How Decidi works
A record of where the labs split, what each side rested on, which disagreements were factual and which were judgement calls, and one moderated verdict with a "verify this" list.
Common questions
How do I get two AI models to disagree with each other?
Put the same question to models from two different labs, then show each one the other's answer and ask it to respond to the reasoning, not the conclusion. The lab matters more than the prompt: two models from the same family share training data and failure modes, so they tend to converge whatever you ask them. Two rounds is usually enough — an opening position each, then a challenge — because most real disagreement appears the moment a model has to defend a claim it made in passing. Decidi runs that structure across four labs by default.
Can I just ask one AI to argue both sides?
You can, and it is useful for mapping the shape of an argument, but it is not the same thing. Both sides are written by the same weights and the same training data, so the opposing case tends to be the version of the opposition that model finds most plausible — which is the version it already knows how to dismiss. It will also reproduce any factual error on both sides, because the error sits in the source rather than the stance. Use it to structure your thinking; do not treat it as verification.
What does cross-lab disagreement show that a model's own self-critique cannot?
It shows which parts of an answer rest on evidence and which rest on one lab's training. A model reviewing its own output uses the same weights that produced it, so a mistake baked into that training is invisible at both steps — it will tidy the wording and walk straight past the wrong fact. A model from a different lab learned different things and fails in different ways, so it meets the error from outside. Where two labs converge independently, you have real evidence; where they split, you have found the part of the question that is genuinely open.
Which two AI models are most likely to disagree?
Independence matters far more than the specific pairing. Take one model each from two different labs — an OpenAI GPT model and an Anthropic Claude model, say — rather than two versions of the same family. The question matters too: well-documented factual questions produce near-total agreement, while questions involving risk appetite, forecasting, ethics or trade-offs produce the most disagreement. If you want an argument, ask the question that has a judgement inside it.
Is it a bad sign when two AI models disagree?
No — it is usually the most useful thing you will learn. Persistent disagreement between independent models marks the spot where the evidence is thin, the question is contested, or the answer depends on a value only you can supply. A single model hides all of that behind one confident reply. Decidi keeps the split on the record and has an impartial moderator explain what it means before committing to a verdict.
Do I need a tool for this, or can I do it manually?
Manually works and costs nothing: paste the question into two or three chatbots, then paste each answer back into the others and ask them to respond to the reasoning. It is slow, and the hard part is what is left at the end — you referee several confident replies, usually by choosing the one you already believed. Decidi runs the whole loop in one pass and commits to a moderated verdict with a "verify this" list, audited by a separate lab first. Chat is free with no account; full Multi-Agent runs sit inside a plan, with Plus at $19/month including 16 runs a month.
Try it on your own decision
Start in chat free, with no account. When the answer matters, put it to GPT, Claude, Gemini and Grok — they debate it, a Final QA audit reviews it, and you get one clear verdict with the open questions named.
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