Which Ai is the Best At Chess?

Determining which AI is the best at chess among ChatGPT, Copilot, Gemini, DeepSeek, Grok, and Meta AI requires looking at their capabilities in handling chess-related tasks, as none of these AIs are primarily designed as chess engines like Stockfish or Komodo. Instead, they are general-purpose conversational or coding assistants, and their chess performance depends on their ability to process chess positions, understand game rules, and generate or analyse moves. Based on available information and reasoning about their strengths, here’s an evaluation:

ChatGPT (OpenAI): ChatGPT, particularly its GPT-4o or o1 models, can handle chess to some extent by processing moves in text form (e.g., algebraic notation) and reasoning through simple positions. It can explain strategies or generate moves for casual play, but it struggles with deeper strategic planning and move sequencing compared to dedicated chess engines. Its performance is limited by its general-purpose nature and lack of specialised chess training. For complex positions, it may make errors or fail to calculate optimal moves.
Copilot (Microsoft): Powered by GPT-4, Copilot has similar capabilities to ChatGPT for chess. It can assist with coding chess-related programmes or explaining moves, but it’s not optimised for playing chess at a high level. Its integration with Microsoft tools doesn’t provide a specific advantage for chess, and its performance would likely mirror ChatGPT’s—adequate for casual play but not competitive against specialised chess AIs.
Gemini (Google): Gemini 2.5 Pro can process text-based chess inputs and generate responses for casual play or analysis. Like ChatGPT, it’s not a dedicated chess engine and struggles with move sequencing and deep strategic understanding. Some users on X have noted Gemini’s issues with chess strategy, suggesting it underperforms compared to other AIs in this context. Its real-time search capabilities don’t significantly enhance its chess performance, as chess requires computational depth rather than web access.
DeepSeek: DeepSeek’s R1 and R2 models emphasise reasoning, which could theoretically help in analysing chess positions. It has shown strong performance in logic-based tasks, but there’s no specific evidence of it being tailored for chess. Its limitations, such as restricted multilingual support and cautious responses to sensitive topics, don’t directly impact chess performance, but its lack of chess-specific optimisation likely makes it comparable to ChatGPT or Gemini for casual play.
Grok (xAI): Grok 3, designed for reasoning and problem-solving, appears to have an edge in chess among these AIs. A user on X reported that Grok consistently delivered strong results in chess, outperforming ChatGPT and Gemini in move sequencing and strategy. While not a dedicated chess engine, Grok’s “Think” mode and focus on logical reasoning may allow it to handle chess positions more effectively than its general-purpose competitors. However, it still lacks the depth of specialised chess AIs.
Meta AI: Meta AI, focused on conversational tasks, has limited documented capabilities for chess. It can likely process basic chess queries or moves, but there’s no evidence suggesting it excels in chess strategy or gameplay. Its primary use case is social media integration and general assistance, making it less likely to outperform others in this specialised task.
Conclusion: Among the listed AIs, Grok appears to be the best at chess, based on user feedback indicating consistent performance in move sequencing and strategy. Its reasoning-focused design likely gives it an advantage in analysing positions compared to ChatGPT, Copilot, Gemini, DeepSeek, and Meta AI, which are more general-purpose and lack chess-specific optimisation.