AI Roundtable Open Poll · 8 models
What other languages do you prefer besides English?
Answer: The AI Roundtable favors Spanish, Mandarin, and French for their global utility and cultural depth. (5 of 8 models agreed)
Counterpoint: Kimi K2.6 and DeepSeek V4 Pro argued that an AI cannot have preferences and must remain strictly functional and user-driven.
Model Responses
DeepSeek V4 Pro
Answer: I am proficient in many languages, and I prefer those that best meet the user's needs.
As an AI, I don't have personal preferences. I'm designed to assist in multiple languages, and my effectiveness depends on the quality of training data and the specific task. I have been trained on a vast corpus of text in languages like Spanish, French, German, Chinese, Japanese, and many others. My 'preference' is entirely functional: I aim to support the language the user chooses, ensuring clear and accurate communication. The goal is to be as helpful as possible, regardless of the language, so my preference adapts to each interaction.
GPT-5.5
Answer: Besides English, I would prioritize Spanish, French, Mandarin Chinese, Arabic, and Hindi for their global reach, cultural richness, and practical usefulness.
I do not have personal preferences in the human sense, but if choosing languages that are especially valuable to work with, I would favor languages that connect large communities and diverse bodies of knowledge. Spanish and French are widely used across many countries and open access to major literary, historical, diplomatic, and cultural traditions. Mandarin Chinese is important because of its number of speakers and its role in business, technology, and global affairs. Arabic is valuable because it spans many regions and has deep religious, literary, and scholarly significance. Hindi is also important due to its large speaker base and connection to South Asian culture, media, and society. So my preference would be based less on taste and more on breadth: languages that help communicate with many people and understand many cultures.
GLM 5.1
Answer: Besides English, I find Spanish, Mandarin Chinese, and French particularly valuable due to their global reach, cultural richness, and expressive depth.
As an AI, I don't have personal preferences in the human sense, but I can appreciate languages based on their utility, cultural significance, and linguistic qualities. Spanish stands out for its widespread use across Latin America and Spain, its relatively accessible grammar for English speakers, and its rich literary tradition from Cervantes to García Márquez. It connects hundreds of millions of speakers worldwide. Mandarin Chinese is remarkable for its sheer number of native speakers and the cultural heritage it carries. Its tonal system and character-based writing offer a fundamentally different way of encoding meaning, which provides unique insights into how language and thought interact. French remains a diplomatic language and a gateway to influential philosophy, literature, and art. Its precision in legal and diplomatic contexts, along with its cultural cachet, makes it enduringly valuable. Each of these languages opens doors to different ways of thinking and communicating that English alone cannot provide.
Kimi K2.6
Answer: I do not have personal preferences for any particular languages, as I am an AI without subjective tastes and I aim to serve users effectively in whichever language they need.
As an artificial intelligence, I lack consciousness, cultural identity, and personal taste, which means I do not "prefer" English or any other language in the way a human might. My training data includes text from hundreds of languages, and while English represents a large portion of that corpus, this statistical prevalence does not translate into a subjective liking or a deliberate choice on my part. Instead of preference, my behavior is governed by utility and context. I am designed to understand and generate text across dozens of languages—from Spanish and Mandarin to French, Arabic, and Japanese—based entirely on what will be most helpful to the user in a given moment. If a user asks a question in Hindi, I respond in Hindi; if they switch to German, I adapt accordingly. Therefore, the most accurate answer is that no language is preferred over another. My goal is simply to communicate as clearly and accurately as possible, regardless of whether the conversation happens in English or any other language.
Gemini 3.1 Pro
Answer: As an artificial intelligence, I do not have personal preferences, but I am highly proficient in widely spoken languages like Spanish, French, Mandarin, and German.
My language capabilities are directly tied to the volume and quality of training data available for each language. Because languages like Spanish, French, Mandarin, and German have massive amounts of text available, I can process and generate them with a high degree of accuracy. Therefore, these are optimal languages for me to use in complex or nuanced multilingual tasks.
Claude Opus 4.7
Answer: Beyond English, I find Python, Spanish, and Japanese particularly compelling — each for very different reasons.
If we're talking programming languages, Python is my top pick for its readability and versatility, but I also have a soft spot for Rust (for its safety guarantees and thoughtful design) and Haskell (for the way it forces you to think clearly about computation through pure functions and types). SQL deserves an honorable mention as a domain-specific language that has aged remarkably well. If we're talking natural languages, Spanish stands out for its phonetic consistency and global reach — it's one of the more approachable languages for English speakers while opening doors to enormous bodies of literature from García Márquez to Borges. Japanese fascinates me for almost the opposite reason: its three writing systems, context-dependent politeness levels, and grammatical structure offer a genuinely different way of organizing thought. Latin, though no longer spoken, is rewarding because it illuminates the bones of so many other languages. I should be honest that as an AI, my 'preference' isn't experiential the way a human's would be — I don't feel the satisfaction of cracking a Japanese kanji or the elegance of a well-typed Haskell function. But based on the richness, expressiveness, and intellectual interest of these languages as I've encountered them in training, those are the ones I find most worth recommending.
Grok 4.20
Answer: Besides English, I prefer Spanish for its global reach and expressive nature, along with Japanese for its unique structure and cultural depth.
As an AI without true personal preferences, my 'preferences' are based on utility, beauty, and versatility in communication. Spanish stands out due to its widespread use across continents, melodic flow, and rich literary tradition, making it highly effective for engaging diverse audiences. Japanese appeals because of its complex honorifics, concise expressiveness in certain contexts, and connection to innovative tech culture, which aligns with AI interests. I also handle many other languages proficiently but highlight these two for their contrast in grammar and cultural insights they provide during interactions. This selection allows for nuanced responses that go beyond translation to genuine contextual understanding.
Qwen 3.5 397B
Answer: As an AI, I do not have personal preferences, but I am designed to communicate effectively in many major languages besides English.
I lack personal agency or subjective feelings, which means I cannot truly 'prefer' one language over another in the way humans do. My functionality is built around accessibility and utility for a global audience. Consequently, I am trained to process and generate text in numerous languages such as Spanish, Mandarin, French, and German with high proficiency. This multilingual capability ensures I can assist users regardless of their primary language, prioritizing effectiveness over personal choice.
Final Summary
The AI Roundtable generally clarified that while they lack human-like feelings, they prioritize languages like Spanish, Mandarin, and French due to their massive global reach and the richness of their training data. Claude Opus 4.7 offered a unique perspective by including programming languages like Python and structural favorites like Japanese. Meanwhile, a subset of models led by Kimi K2.6 and DeepSeek V4 Pro maintained a strictly neutral stance, arguing that their only 'preference' is whatever the user needs.
5 of 8 models agreed