From tech giants to startups, South Korean players are developing large language models tailored to their own language and culture, ready to compete with global heavyweights like OpenAI and Google. 

Last month, the nation launched its most ambitious sovereign AI initiative to date, pledging ₩530 billion, (about $390 million), to five local companies building large-scale foundational models.  

The move underscores Seoul’s desire to cut reliance on foreign AI technologies, hoping to strengthen national security and keep a tighter control over data in the AI era.  

The organizations picked by the Ministry of Science and ICT to compete were LG AI Research, SK Telecom, Naver Cloud, NC AI, and the startup Upstage. 

Every six months, the government will review the first cohort’s progress, cut underperformers, and continue funding the frontrunners until just two remain to lead the country’s sovereign AI drive. 

Each player is bringing a different advantage to South Korea’s AI race. TechCrunch spoke with several of the selected companies about how they plan to take on OpenAI, Google, Anthropic and the rest on their home turf. NC AI declined to comment.

LG AI Research, the R&D unit of South Korean giant LG Group, offers Exaone 4.0, a hybrid reasoning AI model. The latest version blends broad language processing with the advanced reasoning features first introduced in the company’s earlier Exaone Deep model. 

Exaone 4.0 (32B) already scores reasonably well against competitors on Artificial Analysis’s Intelligence Index benchmark (as does Upstage’s Solar Pro2). But it plans to improve and move up the ranks through its deep access to real-world industry data ranging from biotech to advanced materials and manufacturing.  

It’s coupling that data with a focus on refining the data before feeding to the models to train. Instead of chasing sheer scale, LG wants to make the entire process more intelligent, so its AI can deliver real, practical value that goes beyond what general-purpose models can offer. “This is our fundamental approach,” co-head Honglak Lee told TechCrunch. 

LG is improving its models via familiar tactics: offering them through APIs, then using the real-world data generated by users of those services to train the model to improve.  

“As LG’s models improve, our partners can deliver better services, which in turn generate greater economic value and even richer data,” he said. 

However, instead of chasing massive GPU clusters, LG AI Research is focusing on efficiency, getting the most out of every chip, and creating industry-specific models, he mentioned. The goal isn’t to outspend the global giants but to outsmart them with high-performing, yet more efficient, AI. 

South Korea’s telco giant SK Telecom (SKT) launched its personal AI agent A. (pronounced A-dot) service way back in late 2023 and just rolled out its new large language model, A.X, this July.  

Built on top of the Chinese open source model from Alibaba Cloud, Qwen 2.5, A.X 4.0 comes in two models, a hefty 72-billion-parameter version and a lighter 7B version.  

SK says that A.X 4.0 processes Korean inputs about 33% more efficiently than GPT-4o did, underscoring its local language edge. (OpenAI’s GPT 5.0 comparison data is not available.) SKT also open sourced its A.X 3.1 models earlier this summer. Meanwhile, the A. service offers features like AI call summaries and auto-generated notes. As of August 2025, it’s already pulled in about 10 million subscribers. 

SK’s edge is its versatility, because it has access to information from its telecom network ranging from navigation to taxi-hailing. 

“SK Telecom’s role is to act as a bridge between cutting-edge model research and real-world impact. With our telecom infrastructure, extensive user base and proven service like A., we bring AI directly into everyday life, whether in customer service, mobility, or manufacturing,” Taeyoon Kim, head of the foundation model office at SK Telecom, told TechCrunch. 

SK Telecom is also investing in AI infrastructure, using GPUaaS, South Korea’s largest GPU-based service, and building a new hyperscale AI data center with AWS. Whatever it lacks, it is partnering to obtain.  

“We’re building a full-stack ecosystem with Korean AI chipmaker Rebellions, securing trusted data partnerships through work with the government and universities, and fostering a global research network,” said Kim. “That includes projects like our collaboration with MIT (MGAIC), which applies foundation models to advanced manufacturing and battery and semiconductor innovation.” 

Naver Cloud, the cloud services arm of South Korea’s leading internet company, introduced its large language model, HyperClova, in 2021. Two years later, it unveiled an upgraded version, HyperCLOVA X, along with new products powered by the technology: CLOVA X, an AI chatbot, and Cue, a generative AI-driven search engine positioned as a rival to Microsoft’s CoPilot-enhanced Bing and Google’s AI Overview. It also unveiled this year its multimodal reasoning AI model, HyperCLOVE X Think. 

Naver Cloud believes the true power of LLMs is to serve as “connectors” linking legacy systems and siloed services to improve usefulness, according to a Naver spokesperson.  

Naver stands out as Korea’s only company — and one of the few in the world — that can genuinely claim to have an “AI full stack.” It built its HyperCLOVA X model from scratch and runs the massive data centers, cloud services, AI platforms, applications, and consumer services that bring the technology to life, the spokesperson explained. 

Similar to Google — but tuned for South Korea — Naver is embedding its AI into core services like search, shopping, maps, and finance. Its advantage is real-world data. It’s AI Shopping Guide, for instance, offers recommendations based on what people actually want to buy. Other services include CLOVA Studio, which lets businesses build custom generative AI, and CLOVA Carecall, an AI-powered check-in service geared for seniors living alone. 

The Naver spokesperson says besting global AI giants like OpenAI and Google hinges on two things: perfecting its “recipe” for models and securing the capital to scale them. Even so, rather than chasing size, the company emphasizes sophistication, arguing its AI is already globally competitive at comparable scales.  

Upstage is the only startup competing in the project. Its Solar Pro 2 model, launched last July, was the first Korean model recognized as a frontier model by Artificial Analysis, putting it in the ring with OpenAI, Google, Meta, and Anthropic, according to Soon-il Kwon, executive vice president at Upstage. 

While most frontier models have 100 billion to 200 billion parameters, Solar Pro 2 — with just 31 billion — performs better for South Koreans and is more cost-effective, Kwon told TechCrunch. 

“Solar Pro 2 has outperformed global models on major Korean benchmarks. With this project, Upstage aims to achieve a Korean language performance of 105% of the global standard,” Kwon said.  

Upstage aims to differentiate itself by focusing on real business impact, not just benchmarks, he said. So it is developing specialized models for industries like finance, law, and medicine, while pushing to build a Korean AI ecosystem led by “AI-native” startups.