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从阶跃星辰到银河通用:WAIC 参展企业背后的资本迁徙路线

作者:Judy 文章来源:IT桔子

2026-07-21 11:38

作者:Judy 文章来源:IT桔子

2026-07-21 11:38

邦小白快读

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总:本文梳理了2026世界人工智能大会核心参展企业过去18个月的投融资动态,总结了当前中国AI产业的资本流向与发展趋势,核心干货如下:

1. 核心数据:统计的重点参展企业过去18个月累计融资金额突破千亿人民币,大模型赛道累计融资超800亿,具身智能5家头部企业累计融资超300亿,三大赛道均迎来资本密集投入期。

2. 核心趋势:AI产业已经从概念验证进入规模化落地的关键转折期,资本从追捧概念转向看重落地能力,当前呈现五大趋势:赢家通吃效应凸显、具身智能成为新增长极、产业资本取代纯财务投资、国家队资本走向台前、退出通道更加多元。

3. 潜在风险:当前行业也存在三大风险,资本集中头部可能抑制生态多样性、产业资本介入影响企业独立决策、快速融资催生估值泡沫,需要理性看待AI热潮。

总:本文梳理的AI产业资本与发展趋势,可为品牌商把握行业方向、布局AI赋能业务提供参考,核心干货如下:

1. 产业与消费趋势:当前AI已经进入规模化落地阶段,大模型、具身智能、AI芯片是最受资本认可的三大核心赛道,市场对AI赋能产品的需求持续上升,品牌商可结合自身定位,布局AI技术升级产品,抓住产业升级红利。

2. 资本布局启示:当前产业资本取代纯财务投资人成为AI投资主力,更看重技术协同与供应链卡位,品牌商可通过战略投资绑定优质AI技术能力,完善自身产品生态,强化竞争壁垒。

3. 风险提示:当前AI行业资本高度集中头部,存在估值泡沫风险,品牌商布局AI要避免盲目跟风概念,优先选择与自身业务有协同性、可落地的项目。

总:本文梳理了AI三大核心赛道的资本动向,为切入AI相关赛道的卖家提供了机会、风险参考,核心干货如下:

1. 增量市场机会:当前具身智能是AI领域新的超级风口,资本涌入呈现压缩式融资特征,被业内视为下一个汽车级产业,相关上下游配套赛道存在大量增量机会,卖家可提前布局细分赛道。

2. 赛道格局变化:大模型赛道IPO窗口已经打开,资本向具备商业化能力的头部玩家集中,中尾部生存窗口收窄;AI芯片国产替代进入深水区,上市通道拓宽,政策支持力度大,相关配套赛道机会较多。

3. 风险提示:当前AI行业资本集中头部,中小卖家生存空间被压缩,同时快速融资催生估值泡沫风险,卖家需要避开纯概念项目,找准细分落地场景才能获得生存空间。

总:本文披露的AI产业资本动向,为工厂把握AI带来的商业机会、推进智能化转型提供参考,核心干货如下:

1. 生产端新需求:当前人形机器人赛道成为资本新风口,宁德时代、上汽集团等产业链龙头已经下场布局,对上游核心零部件、代工生产、配套加工等环节提出大量新需求,相关制造工厂可提前对接头部企业,锁定增量订单。

2. 商业机会:AI三大赛道都处于高速增长期,大模型端侧部署需求兴起,AI芯片国产替代加速,都为工厂带来了新的配套制造、零部件生产的增量机会,可结合自身产能对接新需求。

3. 转型启示:当前AI已经进入落地阶段,国家队和产业资本都在大力推动AI产业化,工厂可抓住政策和资本支持的机遇,推进自身数字化、智能化转型,提升生产效率与竞争力。

总:本文梳理的AI产业资本动向,清晰呈现了行业发展趋势,为AI相关服务商把握方向、服务客户提供参考,核心干货如下:

1. 行业发展趋势:当前中国AI产业已经从概念验证进入规模化落地关键转折期,大模型、具身智能、AI芯片三大赛道总融资突破千亿,是资本投入的核心方向,赛道增长确定性强,相关服务需求会持续释放。

2. 客户核心需求:不同赛道客户需求差异明显,大模型企业需要对接产业资本绑定落地能力,具身智能企业需要快速融资推进技术落地,AI芯片企业需要长期资金支持研发,服务商可针对不同需求设计差异化服务产品。

3. 风险提示:当前行业资本过度集中头部,存在估值泡沫、生态多样性不足的问题,服务商拓展客户时要优先关注具备落地能力的企业,规避纯概念项目带来的风险。

总:本文披露的AI产业发展与资本动向,为AI相关平台调整招商运营策略、规避行业风险提供参考,核心干货如下:

1. 市场对平台的核心需求:当前大量AI企业处于融资扩张阶段,多家头部企业已经进入IPO或Pre-IPO阶段,企业需要平台对接资本、产业资源、政策资源,平台可针对性推出资源对接服务,满足企业需求。

2. 招商与运营方向调整:当前资本向具备核心技术、落地能力的头部AI企业集中,具身智能、AI芯片是政策和资本双重看好的赛道,平台招商可侧重引入这类优质项目,同时兼顾细分赛道的中小项目,保障生态多样性。

3. 风向规避:当前行业存在资本集中带来的生态垄断风险、估值泡沫风险,平台运营中要警惕纯概念炒作项目,引导多元化生态发展,规避行业泡沫带来的负面影响。

总:本文基于WAIC参展企业的融资数据,梳理了当前中国AI产业的资本动向,呈现了产业发展的新特征,为产业研究提供了一手干货信息,核心内容如下:

1. 产业新动向:当前中国AI产业呈现五大清晰的新趋势,分别是赢家通吃的马太效应加速凸显、具身智能成为产业新增长极、产业资本取代纯财务资本成为投资主力、国家队资本从幕后走向台前、资本退出通道更加多元化,清晰展现了当前AI产业的发展走向。

2. 产业新问题:AI高速发展下也暴露了新问题,包括资本过度集中头部可能抑制产业生态多样性、产业资本深度介入会影响企业独立决策空间、压缩式融资节奏催生估值泡沫风险,这些新问题都值得深入研究。

3. 政策与模式启示:当前AI已经纳入国家战略版图,形成国家队资本+产业龙头+头部VC的联合投资模式,这种模式对培育战略性新兴产业的启示,以及AI产业新的投融资、商业化模式,都为研究提供了新的方向。

声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

我是 品牌商 卖家 工厂 服务商 平台商 研究者 帮我再读一遍。

Quick Summary

This article organizes the financing and investment dynamics of core exhibitors at the 2026 World Artificial Intelligence Conference (WAIC) over the past 18 months, summarizes the current capital flow and development trends of China's AI industry, with key takeaways as follows:

1. Core Data: The cumulative financing of the sampled key exhibitors exceeded 100 billion yuan in the past 18 months. Cumulative financing for the large model track topped 80 billion yuan, and five leading embodied intelligence companies raised over 30 billion yuan combined. All three core tracks are now in a period of intensive capital investment.

2. Core Trends: The AI industry has entered a critical inflection point moving from proof-of-concept to large-scale commercial deployment. Capital has shifted from chasing hype to prioritizing real-world implementation capability, and the industry now presents five major trends: a growing winner-takes-all effect, embodied intelligence emerging as a new growth engine, industrial capital replacing pure financial investment as the main source of funding, state-backed capital moving to the forefront, and more diversified exit channels for investors.

3. Potential Risks: The industry currently faces three major risks: capital concentration at the top may inhibit ecological diversity, intervention from industrial capital can undermine corporate independent decision-making, and rapid financing has fueled valuation bubbles. The AI boom should be approached with rationality.

This article organizes insights on capital dynamics and development trends in the AI industry to help brand owners grasp industry direction and plan AI-enabled business layouts, with key takeaways as follows:

1. Industry and Consumer Trends: AI has now entered the stage of large-scale deployment. Large models, embodied intelligence and AI chips are the three core tracks most favored by capital, and market demand for AI-enabled products continues to rise. Brands can align AI technology upgrades with their own positioning to capture dividends from industrial upgrading.

2. Implications for Capital Layout: Industrial capital has now replaced pure financial investors as the main driver of AI investment, with a greater focus on technological synergy and supply chain positioning. Brands can use strategic investment to bind high-quality AI capabilities, improve their own product ecosystems, and strengthen competitive moats.

3. Risk Warning: Capital in the AI industry is highly concentrated in top players, creating valuation bubble risks. Brands should avoid blindly following hype when planning AI layouts, and prioritize projects with synergy and clear implementation paths aligned with their core business.

This article organizes capital trends across AI's three core tracks to provide opportunity and risk references for sellers entering AI-related segments, with key takeaways as follows:

1. Incremental Market Opportunities: Embodied intelligence is currently the new mega-trend in AI. Capital inflow has taken the form of compressed, fast-track financing, and the sector is widely seen as the next auto-scale industry. There are massive incremental opportunities across its upstream and downstream supporting segments, and sellers can布局 niche areas in advance.

2. Shifting Track Landscape: The IPO window for the large model track has opened, with capital concentrating on top players with proven commercialization capabilities, narrowing survival space for mid- and bottom-tier players. Domestic substitution of AI chips has entered a deep-water phase, with expanded listing channels and strong policy support, creating abundant opportunities in related supporting segments.

3. Risk Warning: Capital concentration at the top of the AI industry has compressed survival space for small and medium-sized sellers, while rapid financing has generated valuation bubble risks. Sellers should avoid pure concept projects, and identify niche implementation scenarios to secure a foothold.

This article discloses capital dynamics in the AI industry to help factories grasp business opportunities brought by AI and advance intelligent transformation, with key takeaways as follows:

1. New Demand on the Production Side: The humanoid robot track has become a new capital hotspot, with industry leaders including CATL and SAIC Motor already entering the space. This has generated massive new demand for upstream core components, contract manufacturing, and supporting processing. Relevant manufacturing factories can connect with leading enterprises in advance to lock in incremental orders.

2. Business Opportunities: All three core AI tracks are in a period of rapid growth. The rising demand for on-device large model deployment and accelerating domestic substitution of AI chips have brought new incremental opportunities for factories in supporting manufacturing and component production. Factories can match their existing production capacity to these new demands.

3. Transformation Implications: AI has now entered the implementation phase, with both state-backed capital and industrial capital vigorously pushing AI industrialization. Factories can leverage opportunities from policy and capital support to advance their own digital and intelligent transformation, improving production efficiency and competitiveness.

This article organizes capital dynamics in the AI industry to clarify industry development trends and help AI-related service providers set direction and serve clients better, with key takeaways as follows:

1. Industry Development Trends: China's AI industry has entered a critical inflection point moving from proof-of-concept to large-scale implementation. The three core tracks of large models, embodied intelligence, and AI chips have raised over 100 billion yuan in total financing, making them the core focus of capital investment. With strong growth certainty, demand for related services will continue to expand.

2. Core Client Demand: Client needs vary significantly across tracks: large model companies need to connect with industrial capital to secure implementation capabilities, embodied intelligence companies require rapid financing to advance technology deployment, and AI chip companies need long-term capital to support R&D. Service providers can design differentiated service offerings tailored to these distinct needs.

3. Risk Warning: Excessive capital concentration at the top of the industry has created problems including valuation bubbles and insufficient ecological diversity. When expanding client bases, service providers should prioritize companies with proven implementation capabilities, and avoid risks from pure concept projects.

This article discloses AI industry development and capital dynamics to help AI-related platforms adjust their investment promotion and operation strategies and mitigate industry risks, with key takeaways as follows:

1. Core Market Demand for Platforms: A large number of AI companies are currently in a phase of expansion via financing, and multiple leading firms have entered IPO or Pre-IPO stages. These companies need platforms to connect them with capital, industrial resources and policy resources. Platforms can launch targeted resource matching services to meet these demands.

2. Adjustments to Investment Promotion and Operation Direction: Capital is concentrating on top AI companies with core technology and implementation capabilities, while embodied intelligence and AI chips are favored by both policy and capital. Platforms can prioritize these high-quality projects in investment promotion, while also supporting small and medium-sized projects in niche tracks to preserve ecological diversity.

3. Risk Mitigation: The industry currently faces risks of ecological monopoly and valuation bubbles driven by capital concentration. In operations, platforms should guard against pure concept hype projects, guide diversified ecological development, and avoid negative impacts from industry bubbles.

Based on financing data of WAIC exhibitors, this article organizes current capital dynamics in China's AI industry and presents new characteristics of industrial development, providing first-hand insights for industrial research, with core content as follows:

1. New Industry Trends: China's AI industry currently presents five clear new trends: the accelerating winner-takes-all Matthew effect, embodied intelligence emerging as a new industrial growth engine, industrial capital replacing pure financial capital as the main investment source, state-backed capital moving from behind the scenes to the forefront, and more diversified capital exit channels. These trends clearly outline the current development trajectory of the AI industry.

2. New Emerging Issues: New problems have emerged amid AI's rapid growth: excessive capital concentration at the top may inhibit industrial ecological diversity, deep intervention from industrial capital can reduce corporate independent decision-making space, and compressed financing timelines have fueled valuation bubble risks. All these new issues warrant further in-depth research.

3. Implications for Policy and Model Research: AI has now been incorporated into China's national strategic layout, forming a joint investment model of state-backed capital, industrial leaders, and top-tier venture capital. The implications of this model for cultivating strategic emerging industries, as well as new AI financing and commercialization models, open up new directions for research.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

作者 |Judy

来源 |IT桔子

2026年7月17日,世界人工智能大会(WAIC)在上海开幕。1100余家参展商、10万平方米展出面积、超过30万专业观众——这是大会的「面子」。

但真正值得深读的,是「里子」:这些参展企业过去18个月的融资表现,正在成为中国AI产业走向的资本晴雨表。

我们通过IT桔子数据平台,系统梳理了本届WAIC核心参展企业在2025年至2026年7月的投融资动态。

大模型、具身智能、AI芯片三大赛道正迎来前所未有的资本密集期——

仅本文统计的重点参展企业,过去18个月累计融资金额已突破千亿人民币级别。

大模型:IPO窗口已开,资本向头部集中

大模型是本届WAIC最吸金的赛道,也是资本逻辑变化最剧烈的领域。

智谱、MiniMax相继完成港股IPO,为大模型行业树立了退出标杆。智谱7月9日完成配售再融资,募资314.10亿港元;MiniMax(稀宇科技)次日跟进,配股+可转债共募资约160亿港元。

尚未上市的企业同样吸金。

阶跃星辰2026年5月完成Pre-IPO轮融资,金额达25亿美元,中兴通讯、华勤技术、腾讯投资、豪威集团、龙旗科技联合注资;

生数科技7月刚完成5亿美元B+轮融资;

面壁智能同月完成数亿人民币E+轮融资;

无问芯穹5月完成7亿人民币B轮融资。

阶跃星辰(StepFun)是这轮大模型融资浪潮中最具代表性的案例。

这家2023年4月成立于上海徐汇的清华系大模型公司,市场预估估值已达120亿美元。

其融资速度令人瞩目:

2023年11月完成A轮数千万美元融资,投资方为五源资本、启明创投、红杉中国;2024年12月B轮融资金额升级至数亿美元,上海国投加入;2026年1月B+轮一举升至50亿人民币,上海国投、五源资本、启明创投、腾讯投资等持续加注;仅4个月后,Pre-IPO轮达到25亿美元,中兴通讯、华勤技术、腾讯投资、豪威集团、龙旗科技联合投资;同月莲花控股领投3亿人民币跟进。

值得关注的是投资方结构的变化。

早期轮次以五源资本、启明创投、红杉中国等纯财务投资人为主;B+轮开始,腾讯连续三轮押注;到Pre-IPO轮,中兴通讯、华勤技术等硬件生态伙伴入场——这标志着产业资本不再满足于财务回报,而是试图通过投资绑定端侧大模型部署能力。

从行业整体看,大模型赛道的融资逻辑正在发生三个转变:

一是IPO通道打开,智谱和MiniMax的上市为后续企业提供了退出预期;

二是产业资本入场,中兴、宁德时代、上汽集团等实体巨头从财务投资转向战略布局;

三是融资节奏从「小步快跑」转向「大额集中」,2026年上半年单笔平均融资额较2025年提升约3倍。

资本正从「看PPT」转向「看落地」,具备商业化能力的头部玩家获得超额溢价。

具身智能:极速「压缩式融资」

如果说2024年是具身智能概念元年,2025至2026年则是资本爆发期。

宇树科技、银河通用、逐际动力、星动纪元、智元机器人等人形机器人领军企业,过去18个月累计吸金超过300亿人民币,且多家已进入Pre-IPO阶段。

银河通用机器人(Galbot)的融资节奏,是这轮具身智能资本热潮中最极端的案例。

这家2023年5月成立于北京海淀、聚焦通用人形机器人的企业,从2024年6月天使轮到2026年3月B+轮,不到两年完成5轮融资,累计金额超过70亿人民币。

具体来看:

2024年6月天使轮7亿人民币,IDG资本、启明创投注资;5个月后的战略投资轮5亿人民币,美团加入;2025年6月B轮11亿人民币,宁德时代、纪源资本入场;同年12月B+轮3亿美元,中国移动、中金资本跟进;2026年3月再获B+轮25亿人民币,上汽集团、国家人工智能产业投资基金、国家集成电路产业投资基金联合注资。

银河通用的投资方演变轨迹清晰呈现了具身智能赛道的资本升级路径:

早期由IDG、启明等头部VC主导,随后美团、宁德时代等产业资本介入,最终国家集成电路基金、国家AI基金等「国家队」入场。

这种「国家队+产业龙头+头部VC」的三重背书结构,说明具身智能已被视为国家战略性新兴产业。

逐际动力的节奏更为紧凑——

2026年7月完成Pre-IPO轮2亿美元融资,距离上一轮B轮仅隔5个月。

这种「压缩式融资」只出现在超级风口期,意味着资本对赛道前景的高度共识,也暗示着企业间的人才和技术竞争正在加剧。

AI芯片:国产替代进入深水区

张江科学会堂作为本届WAIC的「芯算融合馆」,集结了华为、沐曦、燧原科技、摩尔线程、天数智芯等60余家AI芯片企业。

这个赛道的融资逻辑与大模型和具身智能截然不同——更长的研发周期、更高的资金门槛、更强的政策依赖性。

摩尔线程(Moore Threads)是AI芯片赛道最具标志性的案例。

这家2020年6月成立于北京海淀的企业,由前NVIDIA全球副总裁张建中创立,2025年12月5日完成IPO上市,募资80亿人民币,成为「国产GPU第一股」。其股东阵容包括字节跳动、腾讯、红杉中国、五源资本等顶级机构,贯穿了从早期到上市的全过程。

摩尔线程的上市,对AI芯片赛道具有多重意义:

它验证了国产GPU企业走通资本市场路径的可行性,也为后续企业提供了估值参照。2026年2月,爱芯元智紧随其后完成港股IPO,募资29.61亿港元,进一步印证了AI芯片企业的上市通道正在拓宽。

不过,与大模型和具身智能赛道相比,AI芯片领域的融资呈现出不同特征:

部分企业(燧原科技、后摩智能)的最新一轮融资金额未披露,反映出该赛道更高的信息壁垒和更长的商业化周期;

投资方中国有资本和运营商占比较高,市场化VC的参与度相对较低。

这与AI芯片研发周期长、投入大、回报慢的产业特性直接相关。

资本流向全景:钱去哪儿了?

将三大赛道并置对比,可以更清晰地看到资本的分布逻辑。

从上述对比中,可以提炼出五个值得关注的趋势:

第一,赢家通吃效应显著。

阶跃星辰单笔Pre-IPO即获25亿美元,生数科技B+轮5亿美元,资本向Top 5高度集中。

大模型赛道累计融资超800亿人民币,但绝大部分流向少数头部企业。

这一趋势意味着,大模型领域的「马太效应」正在加速——头部企业凭借资金优势扩大算力和人才壁垒,中尾部企业的生存窗口可能正在收窄。

第二,具身智能成为新的增长极。

银河通用9个月5轮融资、逐际动力5个月完成2亿美元Pre-IPO——这种「压缩式融资」只出现在超级风口期。

5家代表企业全部为独角兽,累计融资超300亿人民币。

更值得注意的是投资方结构:上汽集团、宁德时代、蔚来等产业链巨头直接入场,说明具身智能被视为下一个汽车级产业。

第三,产业资本取代纯财务投资人。

中兴通讯投资阶跃星辰、上汽集团注资银河通用、宁德时代押注具身智能、阿里腾讯美团联合投资宇树科技——

这些案例表明,产业资本正在通过投资切入AI产业链的不同环节。与纯财务投资不同,产业资本更看重技术协同和供应链卡位,其入场往往意味着更深度的业务绑定。

第四,国家队从幕后走向台前。

国家集成电路产业投资基金、国家人工智能产业投资基金频繁亮相,在银河通用等项目中与市场化资本联合投资。

这表明AI已被纳入国家战略版图,政府引导资本正在与市场资本形成合力。

第五,退出通道多元化。

除IPO外,并购整合、战略投资等方式增多。

智谱、MiniMax、摩尔线程、爱芯元智相继上市,为后续企业提供了估值参照和退出预期;部分企业则选择引入产业方换取深度协同,而非单纯追求上市。

资本不是万能的

WAIC 2026不仅是一场技术盛宴,更是一次产业实力的集中检阅。

融资数据告诉我们:

中国AI产业正在经历从概念验证到规模化落地的关键转折期。

大模型需要找到可持续的商业闭环,具身智能需要跨越从实验室到工厂的鸿沟,AI芯片需要在外部封锁下实现自主可控。

千亿资本的涌入,说明市场对中国AI产业的前景投下了信任票。

但资本催生的繁荣也伴随着风险:

融资高度集中于头部企业,可能抑制生态多样性;产业资本深度介入,可能影响企业独立决策空间;「压缩式融资」节奏下,估值泡沫的风险不容忽视。

当你在WAIC 2026的展位间穿行时,不妨多想一个问题——

这家公司的投资人在想什么?

答案往往比展板上的技术参数更有信息量。

注:文/Judy,文章来源:IT桔子(公众号ID:itjuzi521),本文为作者独立观点,不代表亿邦动力立场。

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FAQ回顾

2025至2026年中国AI产业资本重点布局哪些赛道?

2025年至2026年7月,中国AI产业资本重点布局三大赛道,分别是大模型、具身智能、AI芯片,仅2026世界人工智能大会统计的重点参展企业过去18个月累计融资金额已突破千亿人民币,资本向头部企业集中趋势明显。

大模型赛道的融资逻辑发生了哪些变化?

大模型赛道融资逻辑出现三大转变:一是IPO通道打开,智谱、MiniMax相继港股上市为行业树立退出标杆;二是产业资本入场,中兴、宁德时代等实体巨头转向战略布局;三是融资节奏从"小步快跑"转向大额集中,2026年上半年单笔平均融资额较2025年提升约3倍。

具身智能赛道融资有哪些典型特征?

2025至2026年是具身智能资本爆发期,宇树科技、银河通用等5家领军企业过去18个月累计吸金超300亿元,多家进入Pre-IPO阶段,出现"压缩式融资"特征,投资方形成国家队、产业龙头、头部VC三重背书结构,被视为国家战略性新兴产业。

AI芯片赛道的融资有什么不同于其他AI赛道的特点?

AI芯片赛道研发周期更长、资金门槛更高、政策依赖性更强,上市通道正逐步拓宽,摩尔线程成为"国产GPU第一股",爱芯元智随后完成港股IPO,投资方中国有资本和运营商占比较高,市场化VC参与度相对较低。

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