MiniMax: A Young Man from a Henan County and His 300 Billion

Title: MiniMax: A Young Man from a Henan County and His 300 Billion

Author: Dongcha Beating

Source:

Repost: Mars Finance

In 2014, Baidu Research Institute had an intern, a PhD from the Institute of Automation, Chinese Academy of Sciences, from a small county in Henan. He calculated for himself: the ideal job after graduation was IBM, coding in Java, with an annual salary of 280,000 yuan.

During the Spring Festival of 2026, a tool called OpenClaw Agent exploded globally. Developers needed a large underlying model to support the lobster. One model was fast and cheap, consuming 1.44 trillion tokens in a week on OpenRouter, topping all platforms.

This model was called M2.5, and the company was MiniMax.

Two months after going public, the stock price soared from HKD 165 to HKD 1,300, with a market value exceeding 300 billion yuan, despite the company’s annual revenue being less than $80 million.

The person behind MiniMax is the same intern from twelve years ago, Yan Junjie.

A Bet Made Over a Year in Advance

During the Spring Festival of 2021, Yan Junjie returned to his hometown in Henan to visit his grandfather.

His grandfather told him he wanted to write a memoir, to record his 80 years of life. But he couldn’t type, nor organize his stories well. After mentioning it several times, he gave up.

Yan Junjie had been working in AI for over a decade. At that moment, he suddenly realized that what he had been doing—helping industries implement AI—was of no use to an elderly person wanting to write a memoir.

This detail was later repeatedly cited, with a bit of an inspirational story vibe. But it truly explained his motivation: to make AI accessible to ordinary people. This obsession later drove a series of counterintuitive decisions.

At the end of 2021, he left SenseTime.

The timing was crucial. SenseTime was preparing for a Hong Kong IPO. He was vice president, deputy director of the research institute, CTO of the Smart City Business Group. He left at a time when the company was most valuable. He didn’t wait for the IPO or wealth realization; he left before that.

ChatGPT was only released in November 2022.

MiniMax was founded in December 2021.

This time gap became the foundation for everything later. Yan Junjie later said that if they hadn’t started early, in the later environment where “star researchers and big tech AI backgrounds are more favored,” MiniMax wouldn’t have been able to compete.

His parents are ordinary people. He studied high school in a county town, then got into Southeast University’s mathematics department, later earned a PhD at the Institute of Automation, Chinese Academy of Sciences, did a postdoc at Tsinghua, and then joined SenseTime. He rose step by step, with no overseas background or prominent connections.

During his internship at Baidu, he interacted with Yu Kai from Horizon Robotics. Yu Kai later said that academic ability can be trained, but engineers who can implement AI technology are rare. Yan Junjie is one of them.

After joining SenseTime, he spent seven years rising from intern to vice president. In 2018, with limited staff, he led a team to develop a model algorithm called “All for One,” which outperformed Megvii and Yitu in competitions, winning industry first place. Someone commented that he “reads papers very quickly, focusing only on the essence, not clichés.” This efficiency later became the company culture at MiniMax.

He named the company MiniMax, inspired by von Neumann’s minimax algorithm in game theory.

His explanation: decision-making should first guard against the worst risks, then choose the relatively optimal solution.

A Peculiar Shareholder Chart

In December 2021, MiniMax completed an angel round, raising $31 million, with a pre-money valuation of $170 million. Investors included MiHoYo, IDG, Hillhouse, and Yunqi.

MiHoYo’s investment was special. Yan Junjie had a good relationship with Liu Wei, chairman of MiHoYo. They invested during the angel round, and Liu Wei remains a non-executive director on MiniMax’s board.

MiHoYo is also a client of MiniMax, using their models for NPC dialogue and story generation in games.

After the angel round, there was a small incident.

In March 2023, Silicon Valley Bank declared bankruptcy. All of MiniMax’s funds were in that bank. It was the riskiest moment early in the startup, with no funds and a chaotic financing environment. But they survived, and two months later secured Series A funding of $257 million, with a valuation of $1.157 billion.

The subsequent investors became increasingly impressive. Alibaba joined, Tencent joined, Sequoia Capital followed. Before going public, they completed seven rounds of financing, raising nearly $1.5 billion in total, with a valuation of $4.2 billion. After IPO, Alibaba held 12.52%, making it the largest external shareholder.

Yan Junjie had a habit in early financing: only negotiate with the top representatives of investment firms. He met with Sequoia’s Shen Nanpeng and Hillhouse’s Zhang Lei.

But on this shareholder chart, there’s one person worth mentioning separately: Yuan Yeyi.

Born in 1994, she graduated with a bachelor’s in electronic engineering from Johns Hopkins University, minoring in economics and mathematics. She joined SenseTime right after graduation in 2017, working on financing and strategic investments. A year later, she became the executive assistant to CEO Xu Li and director of the strategic department. She was deeply involved in SenseTime’s entire journey from early days to Hong Kong listing.

In 2021, she and Yan Junjie started a company together.

An investor commented that she is “capable, commanding, highly driven, with a maturity beyond her age.” Her role with Yan Junjie was clear: one defines the technical vision, the other turns that vision into money and resources. Yan Junjie can dive into technology, even with shaved hair, but the market, capital, and globalization are Yuan Yeyi’s battleground.

On the day of the listing, both stood on the same stage. Yuan Yeyi, 31, valued at over HKD 40 billion.

385 People and 1% of the Money

When MiniMax went public, the company had 385 employees, with an average age of 29.

From founding to September 2025, the company spent about $500 million. During the same period, OpenAI spent between $40 billion and $55 billion.

This comparison is absurd. With less than 1% of the money spent by competitors, they built a globally leading multimodal company. Cost-saving was just the result. The real reason was their relentless pursuit of AI excellence. 80% of the company’s code was generated by AI, internally called “interns,” with permissions high enough to access code repositories, modify online environments, chat in Feishu, review, and deploy directly.

This efficiency made MiniMax’s per capita output abnormally high.

In product development, they adopted a multimodal approach from the start: language, video, speech, music—pushing all four simultaneously. While others were learning ChatGPT for dialogue, Yan Junjie focused on multimodal fusion. He believed that multimodality is the fundamental premise for continuous intelligence improvement. Without it, the next-generation models would have no chance.

In summer 2023, he made a more radical decision.

Allocate 80% of computing power and R&D resources to MoE (Mixture of Experts).

At that time, domestic mainstream models were still iterating dense models. MoE was considered “cutting-edge but immature.” Yan Junjie’s logic was simple: to serve tens of millions or hundreds of millions of users, the cost and latency of token generation with dense models are unsustainable. Without MoE, scale couldn’t be achieved; everything else was pointless.

In early 2024, MiniMax released China’s first MoE large model.

In products, they didn’t compete domestically. For C-end, they launched Xingye and Talkie—one in China, one overseas—focused on AI companionship; Hailei AI for video generation, which in the second half of 2024 maintained the global monthly active user leader in video generation applications for half a year.

Current figures: 236 million users, covering 200 countries and regions, with 73% overseas revenue. 214,000 enterprise clients and developers, with deployments in Google Vertex AI, Microsoft Azure, AWS. Notion’s first open-source model choice was also MiniMax.

In February, ARR surpassed $150 million. The M2 series’ daily token consumption was six times that of December last year, with programming-related growth exceeding tenfold.

This is why the market is willing to give a 200x sales multiple.

But some numbers need to be looked at carefully.

In the annual report, C-end gross profit margin is 4.7%, B-end gross profit margin is 69.4%. 67% of the company’s revenue comes from C-end, but C-end barely contributes to gross profit. Roughly in Q4, C-end gross margin dropped to about 2.1%. Overall gross margin increased from 12.2% to 25.4%, mainly because B-end revenue rapidly increased in Q4, pulling up the overall figure.

This is an unresolved problem.

Mountains are not insurmountable

In June 2025, MiniMax released the M1 model.

Yan Junjie posted a message on WeChat Moments:

“For the first time, I feel that mountains are not insurmountable.”

The reality behind this is that China and the US top-tier model capabilities may only differ by 5%, but that 5% allows overseas companies to dominate scenarios worth ten times more, charge ten times higher prices, and ultimately create nearly a hundredfold business gap. OpenAI’s latest valuation exceeds $700 billion. MiniMax’s market cap at listing is HKD 800 billion, less than $100 billion.

He made a judgment: in the future, there will be five top-tier AGI companies worldwide, at least two from China, and one might even be the leader.

After going public on January 9, he appeared at a symposium hosted by the Premier on January 19, becoming the second AI large model founder after Liang Wenfeng of DeepSeek to attend.

Then, on March 2, the first annual report was released, causing a surge in Hong Kong stocks.

At the earnings presentation, Yan Junjie spent a long time discussing one thing: MiniMax needs to transform from a “large model company” into an “AI era platform company.”

He proposed a formula for platform value: intelligence density × token throughput. In the internet era, platforms are traffic gateways; in the AI era, platforms are companies that define intelligence boundaries and share in the commercial dividends. Google is doing it, OpenAI is doing it, and they want to do it too.

His opponents are dozens of times his size.

Listing in Hong Kong only pushed him into another battlefield. Quarterly reports, analysts, market cap pressures—these are completely different from coding. The secondary market doesn’t believe in sentiment, only numbers. Whether the C-end story can translate into gross profit, whether B-end growth can be maintained, when M3 will arrive—these are questions that must be answered each quarter.

But looking at the bigger picture, MiniMax’s story is more than just a company’s story.

In recent years, the US has tightened chip access. A100, H100, H800—restricted sales. The logic is straightforward: control computing power, control AI.

China has been forced onto a completely different path.

DeepSeek achieved near-H100 performance using H800. MiniMax spent $50 million to do what OpenAI spent hundreds of billions on. Yan Junjie bet on MoE in 2023 because their limited hardware couldn’t support inference for hundreds of millions of users. M2.5 running continuously for an hour costs $1, which is one-twentieth of GPT-5. Innovations like hybrid attention, linear attention, CISPO algorithms are all forced out of necessity.

The chip blockade was meant to widen the gap, but in reality, it pushed Chinese AI companies into a low-compute, high-efficiency evolution route.

Less money, fewer restrictions, fewer people—yet this pushed out extreme engineering capabilities and architectural innovation.

This is similar to Huawei’s chip strategy: block one ability, and I’ll compensate in other dimensions. During this process, new capabilities may emerge that you don’t have.

OpenAI now has over 4,000 employees, spent $8 billion in cash by 2025, and plans to invest $600 billion in computing power by 2030. MiniMax has 385 people and a total investment of $500 million.

Who will win is still unknown. But at least now, fewer and fewer people believe MiniMax will fail.

The Chinese PhD intern at Baidu in 2014 probably never imagined that twelve years later, he would stand at this position, backed by a whole national-level technological competition.

He chose to keep running.