Cantonese AI model built for $250,000 to reach 80 million speakers
Ask any major AI model a question in English or Mandarin, and it will likely answer with fluency and nuance. Ask it something in Cantonese, and the cracks start to show. That gap is exactly what a Hong Kong startup called Votee AI is trying to close, building a Cantonese AI model designed to serve banks, universities, and government departments in a language the biggest AI labs have largely overlooked.
Key takeaways
- Most leading AI models, built by companies like OpenAI, Anthropic, DeepSeek, Moonshot AI and Z.ai, are developed primarily in English and Mandarin because their makers are based in the US or mainland China.
- Cantonese is spoken by more than 80 million people worldwide, yet it has a much smaller pool of standardized digital text than Mandarin, making it a textbook “low resource language” for AI training.
- Votee AI retrains open-weight models such as Meta’s Llama on Cantonese data, growing its training corpus from 100 million to more than 500 million tokens through scraping, community sources and synthetic data.
- Its resulting models run around 70 billion parameters, smaller than frontier systems, and cost roughly $250,000 to train using between 500 million and 1 billion tokens, a fraction of what English-language models require.
- The company frames its work as part of a broader “sovereign AI” push, and is now in talks to expand into Southeast Asia through AI Singapore.
AI’s English and Mandarin Dominance Leaves Cantonese Behind
The current AI boom runs almost entirely on two languages. According to Pak-Sun Ting, CEO of Votee AI, “the whole AI revolution is in English and Mandarin,” and “there’s only a very small fraction that represents other languages.” That imbalance isn’t accidental. The companies leading the field — OpenAI, Anthropic, DeepSeek, Moonshot AI, Z.ai and others — are almost all headquartered in the United States or mainland China, so it’s no surprise their flagship models are strongest in their creators’ native tongues.
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