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2026年芯片融资概览：80 家公司、超 60 亿美元_我的网站

一 |     芝能智芯出品                    2026 年第二季度，芯片融资情况一览。                   钱有的是，主要给了 AI 和它的配套。这一季有 80 家半导体初创企业拿到融资，合计超过 60 亿美元，其中 18 家单轮就破了 1 亿美元。    

    Zhou Jiang speaks at an event. Photo: Courtesy of Zhou Jiang
Zhou Jiang, a researcher at the Sichuan Academy of Social Sciences, has a favorite book:  White Deer Tableland or Bai Lu Yuan by renowned writer Chen Zhongshi.
As vice president of the Regional Science Association of China (RSAC), Zhou told the Global Times that a lifetime of reading has profoundly shaped the way he sees and understands the world. It ultimately led him to a career in research and academia, where he teaches and pursues scholarly work.
Since earning his PhD in economics in 2000, he has devoted himself to the study of regional science and economics, a field that demands a constant crossing of disciplinary boundaries, drawing on the fields of geography, sociology, history, and ecology among others.
"Reading has kept alive my sense of curiosity and taught me to ask questions with patience and persistence: Where do disparities in regional development come from? How do policies affect different groups in society? And how can a region pursue both efficiency and equity so that development is not merely effective, but also imbued with a greater sense of humanity and warmth?" Zhou noted. 
Founded in 1991, RSAC is a national academic society dedicated to advancing domestic and international academic exchange and cooperation, providing consulting services on spatial planning, urbanization, and regional development, and offering intellectual support for China's modernization drive.
The 57-year-old researcher noted that reading has empowered him in two distinct ways.
"The first is discernment. When confronted with a complex issue, I try not to settle for a simple conclusion. Instead, I make an effort to understand its broader context, how it has unfolded, and the perspectives of the different people involved," he said. 
"The second is a sense of inner steadiness. Setbacks are an inevitable part of both life and work. Good books remind us that hardship is never ours alone to bear; countless people before us have faced circumstances more difficult than our own, made difficult choices, and found the strength to carry on. Reading cannot solve every problem for us, but it can help us remain calm when challenges arise, giving us the clarity and resilience that allow us not to panic or give up too easily," he said. 
Historical depth

Each time Zhou returns to the White Deer Tableland, he finds something different in its pages. 
"When I first read it as a young person, I was drawn primarily to the characters and the twists and turns of their lives. Later, as I began researching regional economics, I found myself paying closer attention to the changes in the land, the countryside, families and social order presented in the story. Now, approaching 60, I have come to appreciate more deeply the choices the characters make, the constraints they face, and the quiet perseverance they show amid the sweeping currents of their times," he said. 
White Deer Tableland uses Bai Lu village in Northwest China's Shaanxi Province as a microcosm, tracing the feuds and intertwined fortunes of three generations of the Bai (literally meaning white) and Lu families. Through their stories, it captures more than half a century of sweeping historical change, from the final years of the Qing Dynasty (1644-1911) to the 1970s and 1980s. The novel won the Mao Dun Literature Prize, one of China's top literature awards, in 1997.
Zhou prefers literary works with historical depth and a keen eye for social change. 
Regional economics may appear to be concerned with the spatial distribution of industries, population and resources, but at its heart, it is about how people live on a particular piece of land, and why some places flourish while others decline, he noted. 
In this sense, literature and history are more than pastimes beyond professional research. They often help him understand the historical context, cultural traditions and social mentality that lie behind economic data, he said. 
When reading novels, Zhou said that he often pays close attention to the relationship between people and the places they inhabit: How the land shapes the local character, how transportation transforms a region, and how shifts in industry reshape families and villages. Such details may not offer a direct conclusion, but they broaden a researcher's perspective. They also serve as a reminder that research should look beyond growth rates and statistical indicators to consider the sense of fulfillment experienced by ordinary people and the dignity of human beings.
Understanding ourselves
Once, while tidying his study, he came across a book filled with notes he had scribbled in his early years. Among them was a question that particularly caught his attention: "In the face of sweeping changes in the times and profound social transformation, what can a person truly determine for himself?"
Looking at those words he had written in his youth was like coming face to face with the person he had been decades ago.
Reading is not simply the act of understanding a book; it is also a record of a person's own growth, he said. The same book can reveal something entirely different when read at different stages of life. 
When we are young, we turn to books in search of answers; but when we become seasoned, we read more to understand life, to understand others, and ultimately, to better understand ourselves, Zhou said. 
In this era of fragmented information, AI can help people access information quickly, organize materials, and gain a basic understanding of unfamiliar fields. Yet deep reading, Zhou said, allows people to see how a conclusion is reached — what evidence supports it, where its boundaries lie, and what alternative interpretations it may invite.
What truly shapes a person, after all, is not how much information they have browsed, but the words that have made them pause and reflect - and the words that have remained with them for many years, he added. 
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二 |                    把第一季度的 84 亿美元加进来，光 2026 上半年，全球半导体初创就拿了 140 亿美元出头。                   这堆钱没有平均分给每家公司，少数被看好的方向拿走了大头，剩下的赛道靠边站。                             Part 1           融资的情况，     钱主要去了哪几个方向                    第一季度的画风更猛：同样是 80 家初创，融资冲到 84 亿美元，18 家拿到 1 亿美元以上的 mega-round，Rapidus 和 Cerebras 两家直接摸到了 10 亿美元线。                   从 2025 年第一季度到 2026 年第一季度这五个季度，半导体初创在公开轮次里总共募了超 180 亿美元。

三 |                              钱的分布很不均匀。                   ◎ AI 计算芯片这一个品类，五年里吸走了大约 96 亿美元，是其他任何品类的四倍以上。每个季度排在前三的交易，往往吃掉了当季总额的 57% 到 81%，说明投资人反复把筹码压在少数几张"明牌"上。                   ◎ 另一个信号是资本地板在抬高，AI 芯片赛道里，没有一笔交易低于 2300 万美元，种子阶段的试错窗口正在关上。                             把第二季度的 80 家公司摊开，大致能归成几大块。                             ◎ 最大的一池是 AI 硬件：数据中心大芯片、推理加速器、边缘 AI 硅、还有专门给 AI 做网络互联的芯片。                   过去一年资金几乎都堆在面向数据中心的训练芯片上，这一季边缘端硅重新有了热度，投资人看上了"实体人工智能"和设备端实时应用的前景。

四 |                    ◎ 第二块是处理器与 SoC，里头 RISC-V 最抢眼。                   SiFive 拿到 4 亿美元 G 轮，连英伟达都进来跟投。再往下是光子与光学，薄膜铌酸锂、光路开关、光子 ASIC 这些方向，几乎是每个季度的常客。

五 | 先进封装与 OSAT 也在升温，既有"地缘中立"的新厂冒头，也有 Chiplet 平台继续拿钱。                   ◎ 剩下的板块各有各的戏：制造与设备、EDA 与设计服务、检测量测在往智能化走；功率半导体因为高压、高电压场景被重新重视；传感器、内存存储、量子计算也都有代表交易。量子这一块尤其突出，后面单独说。                   Part 2           分方向盘点：     新公司、新方向、亮点                    ● 方向一：AI 推理芯片，从"训练"转向"把模型跑起来"                    训练热潮过后，资本开始认真押注推理专用的硅。

六 |                    ◎ 最炸裂的一笔来自 Etched，这家公司 6 月底走出隐身，宣布累计融了 8 亿美元，估值 50 亿，还签下了超 10 亿美元的客户合同。                   它的 Sohu 芯片把 Transformer 架构直接烧进硅里，用台积电 N4P 工艺流片，它交付的远不止一颗芯片，连整台机柜都一并设计交付。

七 |                    投资人名单也够唬人：Karpathy、Hinton、李飞飞、Peter Thiel、Jane Street 都在列。                   Etched 的打法是从芯片、封装、PCB、冷板到互连一起设计，它赌的是"早一步做出全栈机柜"比纸面跑分更有用。                   走同一条路的还有不少：                    ◎ 英国 Fractile 拿了 2.2 亿美元，把计算和内存放在同一颗裸片上做存算一体；                    ◎ 新加坡 Acrab 走出隐身就融了 3.5 亿美元以上，做边缘代理 AI 的全栈计算架构；                    ◎ 美国 Upscale AI 融了 1.9 亿美元，专攻 AI 网络互联。

八 |                    一个清晰的转向是，推理芯片过去强调兼容通用 GPU，今年更多公司选择为某类负载定制全栈系统。                   ● 方向二：RISC-V 往数据中心走                    ◎ SiFive 那 4 亿美元 G 轮，明确要加速面向数据中心的 RISC-V CPU 和 AI IP。                   ◎ 韩国 XCENA（前身 MetisX）拿了 1.35 亿美元 B 轮，做基于 RISC-V 的近数据处理（CXL）。                   看点在于，RISC-V 早先是嵌入式和 MCU 的天下，如今开始碰数据中心和 AI 负载，和 x86、Arm 在服务器底座上正面交锋的戏码，慢慢有了苗头。

九 |                    ● 方向三：光子与光互联成了常青赛道                    ◎ HyperLight 拿了 8000 万美元 C 轮，做的是薄膜铌酸锂；                    ◎ nEye 同样 8000 万美元 C 轮，做光子光路开关，瞄准 AI fabric；                    ◎ 英国 CamGraPhIC 拿了 2.486 亿美元政府拨款做光子。                   趋势很清楚：搬数据和算数据，在资本眼里一样重要，光互联几乎每个季度都有交易冒出来。                   ● 方向四：先进封装与地缘再布局                    ◎ 马来西亚的 FusionAP 拿了 200 万美元种子轮，打的是"地缘中立" OSAT 平台的旗号；                    ◎ Singapore 之外，Silicon Box 靠债权融了 7700 万美元继续扩 Chiplet 产能。                   封装被重新估值，根源在"后摩尔"，晶体管越做越小越来越难，把裸片叠起来、封起来的空间反倒大了。                   中国这边对应得更热闹。                   ◎ 武汉的湖北星辰完成超 40 亿元人民币 A 轮，是今年国内先进封装最大一笔，主攻 3D 封装；                    ◎ 无锡华进半导体完成超 12 亿元股权融资，加码 2.5D/3D 集成三期；                    ◎ 长电科技、通富微电、华天科技 2026 上半年合计宣布扩产投资 274 亿元，全部压在 AI 算力核心封装上。                   后摩尔时代，封装成了突破性能瓶颈的一条主路。                   ● 方向五：检测与 EDA 被 AI 重塑                    ◎ 荷兰 Nearfield Instruments 拿了 3.8 亿美元 D 轮，做的是 3 纳米及以下节点的无损在线量测；                    ◎ Invisix 作为 ASML 分拆公司，拿了 2330 万美元种子轮做软 X 射线量测；                    ◎ Cognichip 融了 6000 万美元，做物理感知的 AI 芯片设计；                    ◎ Architect Labs 拿了 2400 万美元种子，做 AI 设计验证芯片。                   有意思的是，AI 不光是芯片的应用对象，也开始反过来加速芯片本身的设计与制造。                   ● 方向六：量子计算爆发                    这一季量子赛道格外亮眼：21 家量子公司完成募资，其中 6 家破 1 亿美元。

十 |                    技术路线也多元，超导、自旋、中性原子、离子阱都有资本下注。Oxford Quantum Circuits 拿了 3.5 亿美元，QuantWare 1.78 亿，Quantum Motion 1.6 亿，Atom Computing 1 亿。                   连低温控制电路、量子芯片检测、量子互联这些配套环节都拿到了钱，说明生态在成形，已经从单点热闹走到了系统布局。                   Part 3           政府和大厂在干什么                    光靠风投撑不起先进制程。                   ◎ 日本对 Rapidus 追加了约 9.43 亿美元政府补贴，专攻 2 纳米厂建设；                    ◎ 西班牙 Openchip 拿到 1.32 亿美元政府投资；                    ◎ 意大利 CamGraPhIC 拿到 2.486 亿美元政府拨款；                    ◎ 澳洲的 NRF 等基金也在扶本土产能。

十一 |                    国家产业政策正在改写半导体融资的地图，Rapidus 和台湾南亚科在 Q1 合计就募了 42 亿美元，靠的是政策背书。

十二 |                    Part 4           对中国芯片行业的读法                    把镜头切回国内。                   2026 上半年，中国一级市场里半导体赛道发生了 611 起融资、估算规模约 408.9 亿元人民币，持续受益于国产替代与产业升级；同期 AI 赛道以 1330 亿元居首，占了全部赛道的三成多。                   江苏年内超 20 家半导体企业拿到融资，近 10 家排队 IPO，无锡研微半导体靠高端薄膜沉积设备拿下近 7 亿元 A 轮，创下当地年内之最；                    碳化硅功率的中瑞宏芯、硅基微显示的芯视半导体也都拿到亿元级融资。                   对照全球盘面，中国在制造、设备、先进封装这些"硬基建"上投入很猛，海外则更多在 AI 推理芯片、RISC-V、量子这些前沿架构上下注，两边形成了一种互补。                    小结               2026 年的芯片融资，主线是 AI 和它的配套，但真正耐看的变化发生在主线的边上。                   边缘硅回暖、光子常青、RISC-V 进数据中心、封装被重估、量子爆发，每一个信号都在说，下一波算力不只会从更先进的制程里来，也会从更聪明的互联、更高效的封装、更专用的架构里来。                   资本已经用钱投了票，剩下的，是看哪条路先把账算平。

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