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Polymind
Prompt
·3 panelists ready·judge:Claude Haiku 4.5

Don't trust one AI. See if the others agree.

Ask once. Up to 7 frontier models answer independently — no coordination, no groupthink. You get an agreement score, the model that dissented and why, then the judge's synthesis of what held up.

How Polymind works

  1. Ask once, in parallel

    Your question goes to every enabled panelist at the same time — up to seven frontier models, answering independently, with no sight of each other's work. Independence is the point: agreement only means something if nobody copied.

  2. See where they split

    Every run scores how much the panel actually converged, names the model that disagreed, and summarizes what it said differently. A split panel is the useful outcome — it tells you the answer you were about to rely on is contested.

  3. Then read the synthesis

    A judge model you choose weighs the panel and writes the final answer. Turn on debate depth and the panelists critique and revise each other first — watching a model change its mind under pressure is often the most informative part of a run.

Frequently asked questions

How do I know if an AI answer is correct?
You can't tell from the answer itself — language models state wrong things in exactly the same confident tone they state right ones. The most practical check available today is independent agreement: ask several frontier models the same question separately and see whether they converge. Broad agreement is weak evidence the answer is safe to act on; a split panel means the question is genuinely contested and you should read the reasoning before trusting any single answer. Polymind runs that check for you in one step.
What does the agreement score mean?
It's how much the panel converged on the same substantive position, judged on meaning rather than wording. High agreement means the models independently reached the same conclusion. Mixed or low agreement is the more useful outcome: it tells you the answer you were about to rely on is not settled. Every run also names the model that dissented and summarizes what it said differently, so you can judge the disagreement yourself instead of taking a score on faith.
How is this different from asking ChatGPT or one chatbot?
A single model has a single set of blind spots, and nothing in its answer distinguishes confidence from correctness. Polymind makes disagreement visible: every run shows an agreement score, flags the panelist that dissents, and lets you read each model's answer side by side before the judge's synthesis. You're not getting one more opinion — you're getting a read on how much the opinion you already have is worth.
What is an LLM council?
An LLM council is a panel of large language models that answer the same question independently, critique each other's answers, and have a judge model synthesize the strongest final answer. Polymind runs your question past up to seven frontier AIs — Claude, GPT, Gemini, Grok, Mistral, Qwen, and Perplexity — in parallel.
Which AI models does Polymind support?
Claude (Anthropic), GPT (OpenAI), Gemini (Google), Grok (xAI), Mistral, Qwen, and Perplexity Sonar, each with a choice of model tier. Any provider on the panel can also serve as the judge that writes the final synthesis.
What are critique rounds?
After the first round of answers, panelists can read each other's responses and revise their own before the judge weighs in — one to three rounds, configurable. Watching a model change its mind under critique is often the most useful signal in the run.
Is Polymind free?
Yes — you can try it without an account, and signing in with Google unlocks the free tier: more models, a larger panel, and critique rounds, with a weekly quota. Premium removes the caps and adds every model tier, deeper debates, web search, and attachments.