Approaching.AI Completes Over 1.3 Billion Yuan Series B Financing, Raising a Cumulative 2.4 Billion Yuan This Year
High-quality AI Token service provider Approaching.AI has completed a Series B financing round of over 1.3 billion yuan, bringing its cumulative fundraising this year to 2.4 billion yuan. This round was co-led by Zhecai Innovation, Xiaoshan Capital, ICBC Investment, and others. The funds will be directed toward expanding high-quality AI Token production capacity, upgrading and iterating the ATaaS platform, and R&D of underlying inference technologies. The company says it has already carried trillion-level leading large models on domestic chips in real production environments, and has established partnerships with companies including SenseTime, Moore Threads, and MetaX.
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Beyond the financing details, the original text also explains Approaching.AI's technical approach of PD heterogeneous collaboration and trading storage for compute on domestic computing power, which can be used to assess the positioning of this type of Token service provider.
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Recently, high-quality AI Token production service provider Approaching.AI completed a Series B funding round of over RMB 1.3 billion; it has raised a cumulative RMB 2.4 billion so far this year. The company says multiple core operating metrics have grown more than tenfold within half a year.
This round was co-led by Zhecai Innovation, Xiaoshan Capital, ICBC Investment, Zhongguancun Science City, Xinglian Capital and Qianjiang Century City. Cloud Creation Capital, Hunan Gaoxin Zongheng, Jiantou Huake, Shenwan Innovation Investment, CITIC Juxin, Zhuhai Technology Industry Group, SenseTime, Wangsu Science & Technology, Gansu Shuzhi, Changjin Holdings, Yuanzhi Future, Qingzheng Xingzhu, Xiaoka Capital and others followed on, while existing shareholder Shangshi Capital continued to invest.
This is another large funding round for Approaching.AI shortly after it completed its Series A round in July this year. As of October this year, the company has completed multiple consecutive funding rounds in 2026, with total fundraising for the year reaching RMB 2.4 billion.
The proceeds from this round will be focused on expanding high-quality AI Token production capacity, upgrading and iterating the ATaaS (Approaching.AI Token as a Service) platform, R&D on underlying inference technologies and new products, and improving commercialization partnerships and delivery systems.
On the business side, Approaching.AI positions itself as a high-quality AI Token service provider. The company says that in the early stage of the Token market, the supply side emphasized Token volume over service quality, rapidly scaling supply through extensive expansion; as the industry focus shifts to Agent-driven closed-loop business implementation and large models gradually carry production-grade core processes, enterprises are imposing production-grade requirements on AI Tokens in terms of intelligence level, response latency, output speed, context completeness and service stability, and the Token market is consequently forming quality tiers.
By the company's definition, high-quality AI Tokens refer to AI Token services anchored in production-grade scenarios that provide high intelligence, low latency, high speed and strong stability, while combining scalable delivery capability with controllable overall cost.
On the technology route, Approaching.AI adheres to fewer models, deep optimization and high quality, focusing on mainstream large models with clear market demand and broad applications, and advancing the engineering implementation of technologies such as full-system heterogeneous collaboration, trading storage for compute, and virtual-real isomorphism.
In terms of domestic computing power, the company has proposed technical solutions including domestic Prefill-Decode (PD) heterogeneous collaboration, high-performance heterogeneous KV Cache conversion, and heterogeneous computing power fusion, and has already put them into production in high-standard production scenarios. The company says that in real production-grade environments, it has achieved domestic chips carrying trillion-level leading large models and large-scale production of high-quality AI Tokens, with overall cost-effectiveness surpassing the world's most advanced computing power.
On the industry ecosystem side, the company has established partnerships with enterprises including SenseTime, Paratera, Hongxin Electronics, Wangsu Science & Technology, Moore Threads, MetaX, and Iluvatar CoreX.
Approaching.AI CEO Ai Zhiyuan says the real barrier in the computing power race is unit energy efficiency and commercial delivery capability, not scale. The company's more than tenfold growth in half a year confirms the potential of the fewer models, deep optimization route. In the future, it will use this round of funding to expand capacity, deepen domestic PD heterogeneous collaboration, and support customers' large-scale implementation with low-cost, high-quality AI Token services. Risk disclosure and disclaimer
Markets carry risks, and investment requires caution. This article does not constitute personal investment advice and does not take into account the specific investment objectives, financial situation or needs of individual users. Users should consider whether any opinions, views or conclusions in this article are suitable for their particular circumstances. Investment based on this is at the user's own risk.