Report: AI Unicorn StepFun's Valuation Doubles in Six Months, Reshaping the 'Big Six' Landscape

The rapid reconfiguration of China’s AI hierarchy sends a clear signal to global investors: capital is chasing velocity over legacy brand recognition. As Shanghai-based StepFun accelerates past established peers, the region’s foundational model race is no longer just about parameter counts—it’s about execution speed and product-market fit. This shift forces Western competitors to reassess not just who has the best technology, but who can deploy it fastest in a highly competitive domestic market.

I think china’s AI valuation shifts reflect a broader move from speculative hype to tangible product deployment. From an APAC angle, stepFun’s rise challenges the assumption that first-mover advantage guarantees long-term dominance in LLMs. Globally, the consolidation of capital around fewer “unicorns” may streamline supply chains but reduces market diversity.

The landscape of China’s top domestic AI startups, once defined by the “Five Tigers” of large language models (LLMs), is undergoing a significant shift. I followed this evolution closely as a low-profile but rapidly advancing company steps into the spotlight with greater momentum.

StepFun, an AI LLM company headquartered in Shanghai and founded by Jiang Daxin, former Global Vice President at Microsoft, is gaining increasing recognition following the debut of its self-developed models and application products, building a growing “snowball” effect.

This site has learned that in the latest financing market, StepFun has become a favorite, currently conducting a new funding round with a valuation of $2 billion.

Interestingly, Alibaba once again appears in rumors regarding potential layout or investment.

In previous investor lists for StepFun, one can see the presence of top-tier venture capital firms such as Qiming Venture Partners and Matrix Partners China.

The term “Five Tigers” was previously an industry shorthand for the leading unicorn startups in China’s domestic LLM sector. These five companies are Zhipu AI, Moonshot AI, 01.AI, Baichuan Intelligence, and MiniMax.

Now, with StepFun’s strong rise, this collective title may need to be updated.

In the future landscape of Chinese foundational model startups, attention may no longer focus solely on the “Five Tigers,” but rather on a new group dubbed the “Six Little Giants.”

(If you have better naming suggestions, please leave a comment below.)

Dual Focus on Technology and Products

StepFun made its public debut relatively late.

Founded in 2023, it did not officially reveal itself to the public until late March this year.

However, over the past three months, this domestic LLM startup has been actively showcasing its capabilities in both technology and product development.

It has also outlined its long-term roadmap toward Artificial General Intelligence (AGI):

Single-modal → Multi-modal → Unified multi-modal understanding and generation → World models → AGI.

Step Series General-Purpose Large Models

Accompanying StepFun’s debut were three large models developed by the company:

• Step-1: A 100-billion-parameter language model
• Step-1V: A 100-billion-parameter multi-modal model
• Step-2: A trillion-parameter MoE (Mixture of Experts) language model

Among these, the 100-billion-parameter Step-1 was successfully trained in just two months, with comprehensive performance surpassing GPT-3.5.

Two months later, in November last year, the 100-billion-parameter multi-modal model Step-1V was completed. The Step-1V model can accurately describe and understand text, data, charts, and other information within images, and perform tasks such as content creation, logical reasoning, and data analysis based on image inputs.

Additionally, it is capable of understanding video content.

In March this year, StepFun became the first domestic startup LLM company to publicly unveil its trillion-parameter model, Step-2, which utilizes MoE technology.

Two ToC Products

I followed StepFun’s product rollout, noting that the company has publicly released two consumer-facing (ToC) products, both open to all users. This dual-track strategy suggests an attempt to capture both utility and engagement metrics simultaneously.

The first is Yuewen (Leap Ask), a chat-based application positioned as a personal efficiency assistant. It supports uploading external documents, features internet connectivity and information retrieval capabilities, possesses multi-modal abilities, and can summarize charts in its outputs. It is currently available for free use on web browsers and mobile apps.

The second product is called Maopaoya (Bubble Duck), an AI open-world platform offering a vast array of intelligent agents, primarily focused on leisure and entertainment. Interested readers are encouraged to experience it firsthand; further details are omitted here.

I think consumer apps often serve as data flywheels for enterprise model refinement. From an APAC angle, free access lowers barriers but raises questions about long-term monetization paths.

Additionally, the LLM-native application “The Player: I Broke the Large Model” (Touhao Wanjiia), which this site recently shared with readers, is also powered by StepFun’s large model technology. This cross-pollination of tech across different user bases indicates a centralized infrastructure approach.

△ On the Ten Thousand Ways to Draw a Penguin

The Microsoft Alumni Network

StepFun’s leadership is not just a roster of names; it is a direct pipeline from the world’s most influential AI lab. I followed the career paths of CEO Jiang Daxin, who moved from MSRA researcher to Microsoft Vice President in charge of WebXT S+D before launching StepFun. His departure signals a shift in talent retention at Microsoft Asia.

Globally, microsoft’s loss is arguably China’s gain in foundational model expertise.

Jiao Binxing, Head of Data, shares this trajectory. A joint Ph.D. candidate from USTC and MSRA, he led Bing’s core search team before leaving with Jiang. His work on automatic mining algorithms for high-quality global websites remains a key asset for StepFun’s indexing capabilities.

Zhu Yibo, Head of Systems, brings infrastructure scale to the trio. After UCSB, he worked at Microsoft, ByteDance, and Google, mastering 10,000-GPU cluster management. This specific experience in large-scale systems is critical for training frontier models efficiently.

The common denominator is clear: all three core members emerged from Microsoft. This “Microsoft-affiliated” structure suggests StepFun inherits not just code, but the operational DNA of Silicon Valley’s largest AI engine. The recent addition of Senior Principal Researcher Duan Nan further solidifies this talent cluster.

I think a concentrated exodus from one lab can rapidly alter regional competitive balances.

API Restrictions and Domestic Alternatives

While StepFun consolidates its team, the global market is tightening access. OpenAI began emailing developers last night to announce that additional measures will be taken starting July 9 to stop API usage from countries and regions not on its supported list. This creates immediate pressure for Asian firms to rely on local infrastructure.

For Chinese developers, this restriction validates the urgency behind StepFun’s rapid valuation doubling. The “Six Little Giants” of LLMs are no longer just competing for domestic market share; they are building a firewall against geopolitical supply chain shocks.

From an APAC angle, geopolitical friction accelerates the decoupling of global AI ecosystems.

I read the original reporting on StepFun’s rise and noted how this talent density contrasts with broader industry consolidation elsewhere. The “Six Little Giants” must keep pushing forward, not just for market dominance, but to ensure technological sovereignty in a fragmented world.