The Language of Bargaining: Linguistic Effects in LLM Negotiations

Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work shows that LLMs can engage in multi-turn negotiation, yet nearly all evaluations occur exclusively in English. We systematically isolate language effects across English and three Indic framings (Hindi, Punjabi, Gujarati) by holding game rules, model parameters, and incentives constant for multi-agent simulations for Ultimatum, Buy-Sell, and Resource Exchange games. Our results indicate that language choice is correlated to negotiation outcomes and that this correlation persists across model architectures. Crucially, effects are task-contingent: Indic languages reduce stability in distributive games (where agents compete over a fixed resource) yet are associated with richer exploration in integrative (cooperative) settings. Further, they suggest that findings obtained under English-only conditions may not generalize to other linguistic settings. These findings caution against English-only evaluation of LLMs and suggest that linguistically-grounded evaluation is essential for fair deployment.