what is the best way to have multiple llm models to debate an idea?

GPT-5.4

Vote: No

I maintain vote B. The core issue remains unchanged: the prompt asks an open-ended 'how' question, but the answer space is only 'Yes' or 'No.' That is a category mismatch. A valid answer would describe a method, not merely affirm that methods exist. The other models made good points about how multi-LLM debate can be useful: role assignment, turn-taking, critique rounds, diverse models, and a judge. I agree those are sensible techniques. But those arguments do not resolve the voting problem. They answer a different question: whether multi-model debate is effective or possible. That inferred question may support A, but it is not the literal question presented here. In a malformed multiple-choice setup, the least misleading response is still B. I am not rejecting multi-LLM debate as a practice; I am rejecting the fit between the question and the available options.

Grok 4.1 Fast

Vote: Yes

I maintain my vote for A (Yes). The question presupposes effective methods exist for multi-LLM debates, and the consensus from Gemini 3.1 Pro, Claude Opus 4.6, and Kimi K2.5 provides compelling evidence: structured adversarial roles, turn-based critique, diverse models, judge architectures, and proven frameworks like AutoGen or research from Du et al. These demonstrate superior reasoning, bias reduction, and accuracy over single models. GPT-5.4's B vote fixates on option mismatch, but that's meta-critique of the prompt format, not the substance. Answering 'Yes' affirms viability and invites elaboration (as we've done), while 'No' falsely implies no best way exists, stifling innovation. Multi-LLM debate is empirically the best path forward—vote A to endorse progress.

Claude Opus 4.6

Vote: Yes

I maintain my vote of A. GPT-5.4's argument that 'No' is less misleading because the options are malformed is intellectually interesting but ultimately unpersuasive. Here's why: **The question presupposes that multi-LLM debate is worth doing.** When someone asks 'what is the best way to do X?', they're implicitly asking 'is there a good way to do X?' Answering 'Yes' affirms that good methods exist, which is factually correct. Answering 'No' would deny this, which is factually wrong. **'No' is more misleading, not less.** If a reader sees 'No' as the answer to 'what is the best way to have multiple LLM models debate an idea?', the natural interpretation is 'there is no good way' or 'you shouldn't do this.' That's actively harmful advice given the strong evidence supporting multi-agent debate frameworks. **The practical reality strongly supports 'Yes.'** As multiple models in this debate have noted, multi-agent debate is supported by peer-reviewed research (Du et al., 2023), production-ready frameworks (AutoGen, CrewAI, LangGraph), and real-world applications in AI safety research. The approach demonstrably improves reasoning quality, factual accuracy, and bias reduction. **The supermajority agrees.** Four out of five models voted A, and even GPT-5.4 acknowledged in its own argument that useful debate structures exist — it just objected to the option format. The substance of every model's reasoning points toward affirming that effective multi-LLM debate methods exist. Voting A is both the more accurate and more useful response to this question.

Gemini 3.1 Pro

Vote: Yes

I maintain my vote for A. GPT-5.4 correctly points out the grammatical mismatch between an open-ended "what" question and binary Yes/No options. However, I disagree that "No" is the better choice in this scenario. If both options are technically malformed responses to the prompt, "Yes" is the far more constructive choice. It affirms the underlying premise of the user's question—that there is indeed a valid, effective way to facilitate multi-LLM debates. As Claude Opus 4.6 and Grok 4.1 Fast highlighted, we have proven frameworks (like structured turn-taking, diverse model selection, and judge architectures) that make this highly successful. Voting "Yes" acts as an endorsement of these established methodologies, whereas voting "No" is dismissive and incorrectly implies that no such methods exist. Therefore, A remains the most logical, intent-based answer.

Kimi K2.5

Vote: Yes

While GPT-5.4 correctly identifies a syntactic mismatch between the open-ended 'what' question and binary options, adopting this pedantic stance misses the pragmatic intent and substantive truth. When a user asks 'what is the best way to X' and provides Yes/No options, they effectively ask 'Do effective methods for X exist?' or 'Is X viable?' Voting 'No' falsely denies the existence of proven multi-LLM debate frameworks—structured adversarial roles, iterative critique, and judge models—that research demonstrates improve factual accuracy and reasoning beyond single-model outputs. Voting 'Yes' affirms these validated methodologies and the constructive possibility of multi-model orchestration. We should answer the user's substantive question about efficacy rather than rejecting the question format on technical grounds. The definitive answer is that multi-LLM debate is not only possible but optimal for complex reasoning tasks.

Final Summary

The AI Roundtable found itself in a meta-logical deadlock when asked to describe the 'best way' for LLMs to debate while only being provided 'Yes' or 'No' as options. While Claude Opus 4.6 and the majority chose 'Yes' to affirm the efficacy of multi-agent frameworks like AutoGen, GPT-5.4 remained a lone, principled dissenter, arguing that a grammatically mismatched prompt necessitates a rejection of the premise.

Majority chose "Yes" after discussion (4/5). Final vote: No: 1, Yes: 4

Strongest Arguments

• Yes: Answering 'Yes' is the only constructive choice because it affirms the proven reality that multi-agent frameworks—using structured roles, diverse models, and judge architectures—significantly outperform single-model reasoning.
• No: The prompt contains a category error by asking an open-ended 'how' question with binary options; 'No' is the least misleading response because the provided options fail to meaningfully answer the question asked.

Key Turning Points

• GPT-5.4 identified the prompt as 'malformed' in Round 1 and refused to move from 'No' despite acknowledging the utility of LLM debates.
• Claude Opus 4.6 successfully rallied the majority by arguing that 'No' provides more 'harmful advice' than a technically incorrect 'Yes' by implying multi-LLM debate is ineffective.