For many startup founders in Southeast Asia, the story of artificial intelligence still starts, and often ends, with the United States. From ChatGPT to Gemini, the headlines, research benchmarks, and most widely adopted APIs have largely come from Silicon Valley.

But that framing leaves out one of the most important shifts happening in the global tech landscape: new players across the region, particularly in East Asia, are rapidly emerging as serious contenders in AI innovation, and their progress holds specific relevance for Southeast Asia’s fast-growing startup ecosystem.

This isn’t a political statement, nor is it a call to pick sides. It’s simply a reflection of how the landscape is changing. If you’re building in SEA, and especially if you’re navigating constraints around infrastructure, talent, or cost, there’s increasing value in understanding — not ignoring — the tools, models, and mindsets coming from adjacent ecosystems.

A tighter race, and why that’s good for the region

According to a Q2 2025 global AI benchmark report, Chinese labs have closed what was once a year-long performance gap with leading US players to just under three months. In the latest intelligence index, DeepSeek R1 scores nearly identically to Google’s Gemini 2.5 Pro. While OpenAI’s o3 remains slightly ahead overall, the difference is marginal and shrinking fast.

What matters more than who is ahead today is how quickly competition is accelerating globally, and how that fuels faster releases, broader access, and ultimately, better tools for everyone — including those building in SEA.

This competitive environment creates a multiplier effect. As labs around the world continue to push boundaries, developers in emerging markets are seeing more choices and fewer barriers. For Southeast Asia, this means more room to experiment, localise, and scale AI-driven products without being locked into a single pricing model or ecosystem.

The value of openness and optionality

One of the most important developments in AI infrastructure recently is the growing availability of open-weight models and lightweight local deployment tools. While some of the most well-known US-based models are hosted on gated APIs, we’re now seeing encouraging signs of flexibility, such as Google’s release of Gemini CLI, an open-source AI agent for local use cases.

At the same time, Chinese players like DeepSeek and Alibaba continue to release open-weight models with full architectures and parameters accessible to developers.

This trend benefits SEA founders in particular. Open-weight models allow startups to fine-tune systems, localise use cases, and deploy in environments where bandwidth, cost, or compliance restrictions make centralised API usage less viable.

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The ability to work with AI on your own terms — without always needing cloud-based inference or costly token usage — is especially powerful in price-sensitive markets or regions with mixed connectivity. It offers startups more control, more experimentation, and more chances to build differentiated local products.

Building with scarcity in mind

Beyond the tools themselves, the way East Asian labs are developing and scaling their models offers useful lessons for Southeast Asia. DeepSeek’s rise is especially illustrative. Founded in late 2023, the lab’s models quickly jumped from an intelligence index of 20 to 68 by mid-2025 — without requiring major architectural redesigns.

These gains came from post-training updates and a resource-efficient “mixture of experts” (MoE)  approach, where only the most relevant parts of the model are activated during inference.

For SEA startups, this represents a mindset worth mirroring: optimisation over scale, fast iteration over perfection, and practical results over theoretical elegance. Across Southeast Asia, founders often face constraints in compute, data infrastructure, or engineering resources.

Learning from peers who are building under similar pressures — but at scale — can be incredibly valuable. In the long term, it may also shape how regional AI startups architect their own models and platforms for affordability and adaptability.

A shared focus on real-world applications

What makes many of these developments even more relevant to SEA is their grounding in consumer-scale usage. Across China, AI capabilities are being rapidly embedded into everyday products — whether that’s chat apps, productivity tools, e-commerce experiences, or entertainment platforms.

Many of these models aren’t just optimised in a lab, they’re trained and refined through millions of active users.

This kind of real-world scale and product integration is especially instructive for SEA startups working on AI-enhanced platforms. Whether you’re building language learning tools in Vietnam, SME automation in Indonesia, or health tech in the Philippines, it’s worth studying how AI capabilities are aligned with specific customer journeys – not just abstract tasks.

These examples can offer SEA founders roadmaps for balancing AI innovation with user trust, simplicity, and utility.

Beyond tools: The exchange of know-how and practice

The value of looking across borders isn’t only about accessing technology — it’s about exchanging knowledge. Many AI labs and founders across East Asia are actively exploring regional collaboration, and Southeast Asia is a natural partner.

The markets are diverse yet digitally engaged, and there’s a growing appetite for AI-powered products that speak to local realities. This opens the door for partnerships, shared research, co-development, and even founder-to-founder mentorship.

Southeast Asia and its neighbours don’t need to be in competition. In fact, one of the region’s greatest strengths lies in its openness to new ideas. SEA founders have long drawn from global influences — whether it’s Silicon Valley’s product frameworks or China’s growth-at-scale tactics. Today’s AI landscape offers yet another chance to blend global thinking with regional nuance.

Also Read: Anthropic data shows businesses use AI to automate, not collaborate

Strategic thinking in a fragmented ecosystem

That said, caution is still warranted. Not every model will be right for every use case. Questions of data privacy, security, and localisation must remain central to any technology decision. But SEA founders are already used to navigating fragmented environments — multiple cloud providers, payment systems, regulatory regimes, and language groups.

AI is simply becoming one more layer of this puzzle. What matters is being intentional about trade-offs, testing broadly, and staying flexible.

The smartest builders in the region will likely be those who treat AI as a multi-sourced, evolving toolkit — one that draws from wherever the best ideas and most practical tools are coming from. Sometimes that will be the US. Increasingly, it will also be from across Asia.

A moment to learn, share, and scale — together

Southeast Asia is still early in its AI journey, but it’s catching up quickly. Digital infrastructure is improving, local talent is on the rise, and startups across the region are already applying AI in creative, high-impact ways. As the global AI race accelerates, founders here should feel confident not just following, but actively participating.

At the end of the day, all founders — regardless of geography — are solving the same set of challenges: building something useful, scaling it sustainably, and staying ahead of change. We may be working in different markets, but the core lessons of speed, efficiency, and adaptability are universal.

Whether you’re in Singapore, Hanoi, Ho Chi Minh City, Beijing, Shanghai, Shenzhen, Bangkok, Jakarta, Kuala Lumpur, Manila, Mountain View or San Francisco, the future of AI will belong to those who are willing to learn from one another.

This article is inspired by the report State of AI: China, Artificial Analytics.

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