[E-Daily Reporter Kim Hyun-ah ] An unexpected outcome emerged in the second round of evaluations for the Ministry of Science and ICT’s Independent AI Foundation Model Project (DOKPAMO).

While Motif Technologies—which had ranked first in the AAII (Artificial Analysis Index), a comprehensive AI model evaluation conducted by the global AI evaluation agency Artificial Analysis—was eliminated, the LG Corp.(003550) AI Research Institute, which had the lowest AAII score, advanced to the third round of evaluation. Upstage and SKTelecom(017670)also passed the second round.

These results do not simply mean that Motif lagged behind in performance while LG Corp. took the lead. They are interpreted as a signal that the competition criteria are shifting toward a comprehensive evaluation of technological capability, practical applicability, and ecosystem expansion potential—factors necessary for models to grow into global frontier AI—beyond merely benchmark performance.

Motif, which ranked first in AAII, was eliminated in the overall evaluation

Motif 3 scored 47 points in the AAII, significantly outperforming Upstage (37 points), SKTelecom (35 points), and LG Corp. (31 points). When converted to the government evaluation’s AAII weighting of 25 points, the scores are as follows: Motif 11.75 points, Upstage 9.25 points, SKTelecom 8.75 points, and LG Corp. 7.75 points.

Motif 3 is a MoE (Mix of Experts) model with a total of 314 billion (314B) parameters, of which approximately 13.2 billion (13.2B) are activated during the actual inference process.

However, the overall evaluation was different. The second-round evaluation was conducted on a 100-point scale, consisting of 40 points for global benchmarks, 35 points for expert evaluation, and 25 points for user evaluation. Of these, AAII accounted for 25 points.

Ryu Je-myeong, Second Vice Minister of Science and ICT, explained, “Although the technical capabilities were outstanding, AAII received a score of 25 points,” adding, “In the usability and applicability categories—which accounted for 75 points and carried significant weight—the company received a lower evaluation compared to other firms.”

The government did not disclose the detailed scores for each company and stated that no single item was the deciding factor in the rejection. It is interpreted that Motif was unable to sufficiently compensate in other evaluation areas for the high model performance it demonstrated in the AAII assessment.

LG Corp. 750B, SKT 688B… The Trend Toward Larger Models in Korea

Domestic AI models are also rapidly scaling up.

LG Corp. AI Research’s K-ExaOne has 750 billion (750B) parameters, while SKTelecom’s A.X K2 has 688 billion (688B) parameters.

Ahead of this evaluation, LG Corp. expanded the scale of its model to more than three times its previous size. The strategy is to secure training and inference technologies for ultra-large models and lay the groundwork to compete in the same “weight class” as global frontier models.

Lim Woo-hyung, Co-Director of LG Corp. AI Research, stated, “It is difficult to narrow the technological gap with global Big Tech using only small models,” adding, “We will continue to take on this challenge with the goal of achieving performance equal to or better than that of models in the same scale category.”

However, the number of parameters alone does not equate to competitiveness. It must be supported by data, training efficiency, inference performance, agentic AI, practical service applicability, and safety.

Global models reach 2–3 trillion parameters… We’ll start by securing 1 trillion parameters

The pace at which global AI models are scaling up is accelerating.

Among publicly released models, China’s Moonshot AI’s Kimi K3 is reported to have 2.8 trillion parameters (2.8T), Alibaba’s Qwen 3.8-Max has 2.4 trillion (2.4T), and DeepSeek V4 Pro is said to be around 1.6T.

In contrast, major closed-source frontier models such as OpenAI’s GPT, Google’s Gemini, and Anthropic’s Claude do not disclose their parameter sizes.

Therefore, it is difficult to conclude that all global frontier models are in the 10 trillion (10T) range. However, with the emergence of models exceeding 1 trillion and reaching the 2–3 trillion range, it is clear that parameter counts in the trillions have emerged as a key benchmark in the next-generation AI competition.

LG Corp.’s 750 billion (750B) parameters are massive by domestic standards, but there is still a gap when compared to the world’s top-tier open models. This is why LG Corp. emphasizes “competing in the same weight class.”

From “No. 1 in Korea” to “Frontier AI”: The Future of the Independent Foundation Model Project

Amid this, the government has also hinted that the next phase of the Independent Foundation Model Project may differ from the existing approach.

Vice Minister Ryu stated, “Given that global frontier companies are advancing model performance exponentially, we have been engaging in ongoing discussions with companies regarding whether the current scale of support and competition format for independent foundation model projects is sufficient to keep pace.”

He added, “There is a consensus that we should move beyond the existing competition format and restructure it in a way that allows for competition with models that are on par with those of global frontier companies.”

The key point is not to develop “the model with the highest score in Korea,” but to secure national-level AI capabilities that can continuously compete with the world’s top models.

Trillion-won Budget Investment… Possibility of Specific Companies Taking the Lead

Frontier AI development requires massive computing resources and capital. Deputy Prime Minister and Minister of Science and ICT Bae Kyung-hoon previously stated that developing a Mitos-class model would require approximately 10,000 of the latest GPUs, with the cost of the GPUs alone amounting to about 3.5 trillion won.

Accordingly, future government support is likely to expand to include not only fiscal investments in the trillions but also a model that combines private companies’ capital, technology, human resources, and data.

Kim Kyung-man, Director General of the Artificial Intelligence Policy Bureau at the Ministry of Science and ICT, remarked during a background briefing that day regarding the Frontier AI project: “Private-sector participation is necessary, and while it is possible to form a special-purpose company (SPC) involving multiple companies, it is also possible for a specific company to lead the project.”

This implies that, moving beyond the “Dokpamo” model—where multiple companies compete under identical conditions—a new model is possible in which companies with technological capabilities, infrastructure, and global collaboration capacity lead the development of frontier-level AI, while the government provides support for large-scale computing and R&D.

From “Who’s Number One?” to “Who Will Create the Next AI?”

From this perspective, the government plans to provide Upstage, SKTelecom, and LG Corp. AI Research—which all passed the second round of the Dokpamo evaluation—with 40 billion won and 1,000 GPUs each to help improve model performance by the end of the year.

While the existing competition format—in which one company is eliminated at the end of the year—will be maintained, there is a possibility that once inter-ministerial budget negotiations for the development of frontier-level models are completed, the third round of the Dokpamo evaluation will be eliminated. Instead, a plan to integrate Dokpamo with the “Frontier AI” project—which aims to develop models with parameters in the “jo” range and a scale of up to 10 trillion (10T)—will be considered.

Motif’s elimination and LG Corp.’s advancement in this round indicate what the next phase of competition in the Dokpamo project will entail.

Motif demonstrated overwhelming technical prowess in the AAII with its 314B (314 billion) model. LG Corp. advanced to the third evaluation by scaling up its model to 750B (750 billion) and highlighting its comprehensive competitiveness in areas such as global collaboration, agentic AI, and safety. SKT has also joined the race for larger-scale models with a 688B (688 billion) model.

Going forward, the competitive criteria for the “Domestic AI Championship” are increasingly likely to shift from “who received the highest score in this evaluation” to “who can continuously develop global frontier AI.”

Amid discussions about government investments in the trillions and the potential for private-sector leadership, observers note that the competition has reached an inflection point: it is shifting from a contest to determine the “best domestic AI model” to a national-level race to secure AI capabilities capable of actually competing with the frontier AI systems of the United States and China.