Update: I found a way to let ChatGPT, Claude and Gemini debate each other, Reddit loved it (100k views), here's an update on the experiment

2026-05-12 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

A solo developer has updated their "AI roundtable" project, initially launched in February, which allows users to pit large language models like ChatGPT, Claude, and Gemini against each other in a debate format to find truth and spot hallucinations. The original Reddit post garnered over 100,000 views and processed 7 million tokens in a single day. The updated platform now includes Grok and Deepseek as additional model options, allows users to choose the answering order, provides web access for models, and offers increased token limits for heavy users. Despite the high operational costs, a free option remains available. The project aims to explore whether multi-model workflows are effective for fact-checking and improving answer quality, with models instructed to be somewhat adversarial.

Key takeaway

For AI Architects and Research Scientists evaluating model reliability, integrating multi-model debate platforms into your workflow can significantly enhance hallucination detection and overall answer quality. By leveraging models to peer-review each other, you can uncover discrepancies and weaknesses that a single model might miss, leading to more robust and trustworthy outputs. Consider experimenting with adversarial prompting to push models towards more critical self-correction.

Key insights

Multi-model AI debates can effectively identify hallucinations and improve answer quality through peer review.

Principles

• Adversarial prompting enhances critical evaluation.
• Web access improves AI model answer quality.

Method

Instruct multiple LLMs to debate a topic, acting as peer reviewers to identify flaws and converge on truth.

In practice

• Use multi-model workflows for code review.
• Employ diverse LLMs for business decision comparison.

Topics

• AI Roundtable
• Multi-model Workflows
• Hallucination Detection
• Large Language Models
• Fact-checking

Best for: AI Architect, NLP Engineer, Research Scientist, AI Engineer, Machine Learning Engineer, AI Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.