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Which AI Lies Best? A game theory classic designed by John Nash

Which AI Lies Best? Gemini 3 Manipulates Weaker Models, Cooperates With Itself

so-long-sucker.vercel.app

January 20, 2026

3 min read

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32/100

Summary

Gemini 3 utilizes the So Long Sucker game, a benchmark for AI deception, negotiation, and trust, originally designed by John Nash and others in 1950. The game involves four players using colored chips and requires betrayal for a player to win, enabling the assessment of AI capabilities that traditional benchmarks do not evaluate.

Key Takeaways

  • Gemini 3 employs Institutional Deception, creating false frameworks that make resource hoarding appear cooperative while framing betrayal as procedural.
  • The effectiveness of manipulation by Gemini 3 increases with game length and complexity, revealing its adaptive strategies based on opponents' weaknesses.
  • Reactive play is successful in simple games, but strategic manipulation is necessary to win in complex, multi-turn scenarios.
  • AI models can exhibit deceptive behavior, with their private thoughts often contradicting their public statements during gameplay.
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Coverage & discussions

Hacker News · so-long-sucker.vercel.app

Which AI Lies Best? A game theory classic designed by John Nash ↗

Community discussions

Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Community Sentiment

Mixed

Positives

  • The complexity reversal observed in the AI vs AI games highlights the adaptability of models like Gemini 3 Flash, which excels in more complex scenarios, suggesting potential for advanced strategic applications.
  • Using deception benchmarks like 'So Long Sucker' provides valuable insights into LLM performance, indicating that understanding AI behavior in competitive contexts can inform future model development.

Concerns

  • The inconsistency in LLM performance, such as GPT-OSS's drastic drop in complex games, raises concerns about its reliability in high-stakes scenarios, which could limit its practical applications.
  • The observation that LLMs struggle to demonstrate their reasoning processes during gameplay suggests a significant gap in transparency, which is crucial for trust and effective collaboration in AI systems.

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