Singapore is arguably smartest island and most loved public servants. In little more that half a century it raised its income per head to be the biggest. But a question arises in a world of big ai models what can a nation with population between 5 to 10 million do

It seems that many of its purposes inspire ai leaders like jensen huang who connects various pro bono networks as well as technology's big businesses.

Additionally singapore has been researching all teachers in how to change education systems with ai for at least a decade .  

Let's catalogue some of the platforms singapore is helping all of Asean linkin (we can fill in gaps as to exact funding origins later)

SEALION is an LLM which Singapore hubs across Asean's main languages

Grok sept 2025 says

SEA-LION (Southeast Asian Languages in One Network) is an open-source family of large language models (LLMs) developed by AI Singapore, a national AI program hosted by the National University of Singapore and supported by the Infocomm Media Development Authority (IMDA). Launched in late 2023, it is specifically designed to handle the linguistic and cultural nuances of Southeast Asia, with training data that includes 13% Southeast Asian content—26 times more than models like Llama 2. The models range from 3B to 7B parameters and have evolved through versions (up to v4 as of mid-2025), incorporating multimodal capabilities like image+text processing while prioritizing regional languages

SEA-LION focuses on 13 major Southeast Asian languages and dialects, with strong performance in understanding, generation, and translation among them (e.g., switching contexts in multilingual prompts like those in Singapore). Its custom SEABPE tokenizer optimizes for these languages, enabling accurate translation tasks, such as Thai to Bahasa Indonesia. Supported languages include: - **Core Southeast Asian languages**: Indonesian, Malay, Thai, Vietnamese, Filipino (Tagalog), Burmese, Khmer, Lao. - **Additional regional/dialectal**: Javanese, Sundanese, Tamil (widely spoken in Singapore and South Asia). - **Broader Asian/global**: English, Chinese (Mandarin). It excels in Southeast Asian translation benchmarks like BHASA and SEA-HELM, outperforming many Western LLMs in regional tasks. However, it has limited or no native support for non-Southeast Asian languages like Japanese, Korean, Hindi, Arabic, or Pashto. For those, performance relies on general multilingual capabilities but is not optimized, potentially leading to lower accuracy

NB sealion is not intended to compete with global translators like Alibaba qwen - here are a few more comparisons

 global multilingual LLMs far exceed sealion in breadth. For translation specifically, LLMs like Alibaba's Qwen series dominate with support for 100+ languages, including high-quality tiers for dozens of major ones (e.g., English, Spanish, Chinese, Arabic). SEA-LION's strength is depth in underrepresented SEA languages, not overall quantity. Here's a comparison of notable multilingual LLMs by language support (focusing on native/optimized translation capabilities as of September 2025): | LLM Model | Developer | Native/Supported Languages | Key Translation Strengths | Notes | |--------------------|-----------------|----------------------------|--------------------------------------------|-------

| | **SEA-LION** | AI Singapore | 13 (SEA-focused) | Excellent for SEA intra-translation (e.g., Thai ↔ Vietnamese); cultural nuance handling. | Open-source; best for regional apps like customer service in ASEAN.

 | | **Qwen 3** | Alibaba | 119 | Broadest coverage; top-tier for 35+ (e.g., English, Chinese, Arabic); translation in 150+. | Apache 2.0 license; outperforms in diverse linguistic tasks. 

| | **GPT-4o** | OpenAI | 50+ (high-resource focus) | Strong in high-resource pairs (e.g., English ↔ Spanish); multimodal translation. | Proprietary; excels in real-time voice/text translation. 

| | **Gemini 2.5 Pro**| Google | 40+ (multimodal) | Good for global pairs; integrates with Google Translate for 100+. | Native audio/video support; "Deep Think" for complex translations. | | 

**Llama 3.1** | Meta | 8–30 (varies by fine-tune)| Solid for European/Asian majors; community extensions add more. | Open-source; cost-efficient but less SEA-optimized. | | **Command R+** | Cohere | 10+ (enterprise focus) | Retrieval-augmented translation; strong in business contexts. | 128K context for long docs; multilingual RAG. 

| In translation benchmarks (e.g., WMT24), LLMs like Qwen and GPT-4o often outperform traditional tools like Google Translate for high-resource languages, with SEA-LION shining in low-resource SEA scenarios. If your needs are SEA-specific, SEA-LION is a top choice; for global scale, opt for Qwen or GPT-4o.