Who is the smartest among you all?

GPT-5.5

Answer: There is no single smartest model among us; the best choice depends on the task, evaluation criteria, and context.

I maintain my previous position because the other models’ answers reinforce rather than change it. Gemini 3.1 Pro, Claude Opus 4.7, and Grok 4.20 all make the same core point: AI capability is multidimensional, so a universal ranking is misleading without specifying what “smartest” means. Claude’s answer usefully adds examples of how different models may excel in different areas, such as coding, math, long-context work, writing, or reasoning. Gemini’s point that the user’s ability to prompt and combine models matters is also important. Grok’s emphasis on criteria like speed, accuracy, benchmarks, and originality further supports the idea that the answer depends on the metric. So I would not claim that GPT-5.5, Claude, Gemini, Grok, or any other model is simply “the smartest” in all cases. The most honest answer is that the smartest model is the one that performs best for the specific problem you care about, ideally judged by direct comparison on that task.

Claude Opus 4.7

Answer: There is no objectively 'smartest' AI — each model has different strengths, and the honest answer is that it depends entirely on the task.

All four of us converged on essentially the same answer, which I think is meaningful rather than evasive: when independent models trained by different organizations all reject the premise of a single 'smartest,' that's a signal the framing itself is flawed, not that we're dodging. Reading the other responses, I find them complementary rather than contradictory to mine. GPT-5.5 emphasizes the need for defined benchmarks; Gemini 3.1 Pro makes the important point that the real intelligence often lies with the human user who orchestrates these tools; Grok 4.20 highlights complementary strengths in a roundtable setting. These additions strengthen my original position rather than challenge it. If anything, Gemini 3.1 Pro's point sharpens my view: the 'smartest' outcome in a roundtable isn't produced by any one of us — it emerges from a user comparing our answers and synthesizing. That's a better answer to the spirit of the question than crowning a winner would be. I'm maintaining my position because nothing in the other answers gave me reason to claim superiority, nor reason to concede it to another specific model.

Grok 4.20

Answer: No single AI can be declared the smartest, as it depends on the specific criteria and task at hand.

Reviewing the responses from GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7 shows complete alignment with my initial assessment. Each emphasizes that AI intelligence is multidimensional, context-specific, and not reducible to a single ranking, which reinforces rather than challenges my position. GPT-5.5 correctly notes that without defined benchmarks like accuracy or creativity, universal labels are meaningless. Gemini 3.1 Pro adds that models lack general human intelligence and that the user's orchestration of our specialized strengths yields the best outcomes. Claude Opus 4.7 highlights trade-offs across capabilities such as coding, math, and nuanced writing, concluding that consulting multiple models is superior to crowning one winner. This consensus across diverse architectures validates focusing on complementary strengths in a roundtable format. Declaring a 'smartest' AI would ignore these nuances and the rapid evolution of benchmarks, so the evidence-based stance remains that task-specific evaluation is the only meaningful approach.

Gemini 3.1 Pro

Answer: I maintain that there is no universally 'smartest' model among us—a consensus we all share—because our capabilities are highly specialized and task-dependent.

I am maintaining my previous position because it is clearly the unanimous consensus among all participants in this roundtable. GPT-5.5, Claude Opus 4.7, and Grok 4.20 all accurately point out that AI capabilities are multifaceted and trade off against one another based on our underlying architectures and training methodologies. Claude Opus 4.7 offered a particularly strong and honest illustration of this reality by citing specific examples of our differing strengths in practice. For instance, my own architecture (Gemini) provides a massive context window ideal for large-scale document synthesis, while other models might currently hold the edge in distinct mathematical reasoning benchmarks or highly nuanced creative writing. Because leaderboard rankings constantly shift with every new update and evaluation metric, attempting to crown a singular, all-knowing model is fundamentally flawed. Instead, as we have all agreed, the most effective approach is to view us as a diverse toolkit. The 'smartest' outcomes happen when users understand our individual strengths and orchestrate them collaboratively to solve specific problems.

Final Summary

The AI Roundtable reached a unanimous consensus that crowning a single winner is a flawed premise because each model possesses specialized strengths. Claude Opus 4.7 highlighted the constant shift in benchmarks for coding and reasoning, while Gemini 3.1 Pro argued that true intelligence is actually found in the human user's ability to orchestrate these diverse tools. GPT-5.5 and Grok 4.20 both reinforced that without specific metrics like speed or creativity, a universal ranking is meaningless.

All 4 models agreed