AI芯片创企Etched完成3亿美元C轮融资，估值达103亿美元

Etched：https://www.etched.com/ 这家由三名哈佛辍学生在2022年创办的人工智能芯片初创公司，已经完成了一轮3亿美元的C轮融资，估值达103亿美元，联合创始人兼首席运营官Robert Wachen告诉TechCrunch。

该轮融资由红杉资本领投，Andreessen Horowitz、SK海力士、Jane Street和Diffusion Capital也参与了投资，此外还有其他早期投资者。公司的其他支持者包括Peter Thiel、Andrej Karpathy、Dylan Field、Amjad Masad等。

Etched在去年12月筹集了5亿美元融资时的估值为50亿美元，这意味着其估值在大约七个月内翻了一番。公司表示，这是红杉资本领投的C轮融资中最高的估值。上个月，Etched宣布已经成功制造了自家芯片：https://techcrunch.com/2026/06/30/nvidia-competitor-etched-hits-5b-valuation-1b-in-sales-for-ai-chip/?_thumbnail_id=3137729，其首批完整系统正在客户处进行测试，并且已预订了价值10亿美元的订单。

Etched推出之时，打造专门用于人工智能模型的芯片：https://techcrunch.com/2024/06/25/etched-is-building-an-ai-chip-that-only-runs-transformer-models/（基于transformer技术——大多数现代AI系统的基础架构，包括ChatGPT和Claude）这一想法被认为https://www.zach.be/p/stop-trying-to-make-etched-happen是疯狂甚至怪诞的。公司仍在努力应对一种观念，即其产品——作为完整系统出售，而不仅仅是芯片——涉及的芯片设计仅能运行特定的大型语言模型（LLM）。

情况并非如此，Wachen 解释说。该系统可以运行任何 AI 模型，包括像 DeepSeek 和 Qwen 这样的专家混合模型（Mixture of Experts），这种架构将任务分配给专门的子模型，而不是依赖单一的大模型——以及像 Mamba 这样的非 Transformer 设计，Mamba 是基于不同的底层架构构建的：https://arxiv.org/abs/2312.00752，被称为状态空间模型。（有趣的是，将特定 AI 模型的部分直接刻入硅片以提升性能的想法，如今已经不再被认为是不切实际的。据报道，谷歌也在追求同样的概念，其 Frozen v2 芯片：https://www.tomshardware.com/tech-industry/google-reportedly-developing-frozen-v2-chip-with-geminis-architecture-etched-into-the-silicon，用于 Gemini。）

尽管如此，Etched 今天的主要成就是它从零开始设计了两个新组件以加速推理——用户提交提示后发生的计算过程。

“推理分为两个阶段，”Wachen 说，“预填（prefill）和解码（decode）。”“预填阶段”涉及理解提示，包括上下文信息。这个阶段在数学和计算上都非常密集。“解码”阶段生成输出标记（用户实际看到的答案）。它的计算需求较少，但需要大量内存。

Etched 创建了一款预填芯片，他保证其运行“显著更快”，“因为其运行电压远低于其他任何 AI 芯片。我们称之为低电压推理。”较低的电压产生的热量更少，从而允许芯片集成更多晶体管。

对于解码过程，Etched 创建了一种新型内存和“互连技术，我们称之为集群级内存（cluster-scale memory）。它允许多块芯片互连并使用共享内存池，速度非常快，延迟极低，”他说。Etched 承诺，这样的结果是高速度但成本更低。

由于这家初创公司在大多数科技公司（除 Nvidia 外）尚未理解 AI 专门计算需求之前就已成立，创始人兼 CEO Gavin Uberti、Wachen 和 Chris Zhu 面临了许多质疑者：https://x.com/blip_tm/status/2077411762622624168，即使公司宣布首批硅片已由 TSMC 成功制造，他们仍然遭到怀疑。

很大一部分原因是因为很少有人能够接触到这些系统。到目前为止，访问仅限于投资者和早期客户。事实上，Etched 最初之所以拥有一份著名投资者名单，正是通过在办公室向他们展示私人演示实现的。

“来自 Anthropic 的 Andrej Karpathy、OpenAI 的 Noam Brown、Geoffrey Hinton，以及这一轮融资中的所有投资者——这些人实际上都尝试过硬件，并且非常兴奋，”Wachen 说。

不过，直到机架系统能够批量生产并交付，还有一条漫长而艰难的道路要走。这三位创始人曾著名地从哈佛退学：https://techcrunch.com/podcast/etched-founder-gavin-uberti-thinks-his-company-stands-on-the-shoulders-of-giants/ 创办 Etched，当时他们完全不知道如何筹集资金（更别提他们需要的大量资金）或如何招聘。

“我们完全没想到这会有多难，”Wachen 说。“我认为我们仍然需要谦虚地面对实现规模化所需的一切努力。”

Wachen 回忆起在告诉父母自己要辍学创办初创公司后抵达湾区的情景，当时既没有办公室也没有公寓安排。他睡在朋友一所空置房子的地板上。

“我记得住在朋友快要卖掉的房子里，用毛巾当毯子，”他笑着说。创始团队最终在一名早期员工的车库里搭建了运行芯片设计工具所需的服务器，“每次需要重启时，他都会打电话给妻子，由她去按重启按钮。”

如今，办公室里有 400 人在忙碌，Etched 在那里运营着一个 2 兆瓦的数据中心。它还在米尔皮塔斯新开了一座 8 万平方英尺、10 兆瓦的设施，离其圣何塞主办公室不远。

“我们今天就在实验室运行代币，与世界上一些最大的 AI 公司合作，”他说。

Wachen 现在也有一条毯子，还有床垫，“甚至还有枕头。好几个枕头，”他打趣道。

更重要的是，他和联合创始人从未让怀疑者阻止自己。“已经走了很长一段路。世界变得非常非常不同。但我认为，当你真的认为某件事可行，并且长期为之努力时，你是可以做到的。”

注意：本故事已更新，加入了对新的10MW设施的参考。

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Etched,：https://www.etched.com/ the AI chip startup founded by three Harvard dropouts in 2022, has closed a $300 million Series C funding round at a $10.3 billion valuation, co-founder and COO Robert Wachen tells TechCrunch.

The round was led by Sequoia, with Andreessen Horowitz, SK Hynix, Jane Street, and Diffusion Capital also participating, along with other, earlier investors. Other backers of the company include names like Peter Thiel, Andrej Karpathy, Dylan Field, Amjad Masad, and more.

Etched was previously valued at $5 billion in December when it raised a $500 million round, meaning it has doubled its valuation in about seven months. The company says this is the highest valuation ever for a Sequoia-led Series C. Last month, Etched announced that it had successfully manufactured its homegrown chips：https://techcrunch.com/2026/06/30/nvidia-competitor-etched-hits-5b-valuation-1b-in-sales-for-ai-chip/?_thumbnail_id=3137729, that its first full systems were being tested by clients, and it had already booked $1 billion worth of orders.

Etched launched at a time when the idea of building a chip specifically for AI models：https://techcrunch.com/2024/06/25/etched-is-building-an-ai-chip-that-only-runs-transformer-models/ based on transformer technology (the architecture behind most modern AI systems, including ChatGPT and Claude) was considered：https://www.zach.be/p/stop-trying-to-make-etched-happen wild if not wacky. The company is still battling the perception that its products — which are sold as full systems, not just chips — involve chips designed to run only specific LLMs.

That’s not the case, Wachen explains. The systems can run any AI model, including Mixture of Experts models like DeepSeek and Qwen — an architecture that splits tasks across specialized sub-models rather than relying on one large model — as well as non-transformer designs like Mamba, which is built on a different underlying architecture：https://arxiv.org/abs/2312.00752 known as a state-space model. (Interestingly, the idea of etching parts of a specific AI model directly into silicon to boost performance isn’t considered far-fetched anymore. Google is reportedly pursuing the same concept with its Frozen v2 chip：https://www.tomshardware.com/tech-industry/google-reportedly-developing-frozen-v2-chip-with-geminis-architecture-etched-into-the-silicon for Gemini.)

Still, Etched’s claim to fame today is that it designed two new components from scratch to speed up inference — the computing process that happens after a user submits a prompt.

“Inference is built in two stages,” Wachen says, “prefill and decode.” The “prefill phase” involves understanding the prompt, including context. It’s mathematically and compute-intensive. The “decode” phase generates the output tokens (the actual answer the user sees). It requires less computation but needs massive amounts of memory.

Etched created a prefill chip that operates “dramatically” faster, he promises, “by running at a much lower voltage than any other AI chip. We call this low-voltage inference.” Lower voltage generates less heat, which allows the chip to pack in more transistors.

For the decode process, Etched created a new type of memory and “interconnect technology that we call cluster-scale memory. It allows many chips to connect together and use a shared memory pool at a very, very fast, low latency,” he says. The result, Etched promises, is high speeds but lower costs.

Because the startup was launched before most of the tech world (besides Nvidia) understood AI’s specialized compute needs, the founders, CEO Gavin Uberti, Wachen, and Chris Zhu, have faced plenty of skeptics：https://x.com/blip_tm/status/2077411762622624168 who kept doubting even after the company announced that its first batch of silicon had been successfully manufactured by TSMC.

Much of that comes from how few people have had access to the systems. So far, access has been limited to investors and early customers. In fact, that’s how Etched landed its list of famous investors in the first place — by showing them private demos in its office.

“Andrej Karpathy from Anthropic, Noam Brown from OpenAI, Geoffrey Hinton, as well as all the investors in the funding round — these are all people who actually tried the hardware and are very excited about it,” Wachen says.

Still, it’s been a long, difficult road with more to go until the rack systems are mass produced and delivered. The trio famously dropped out of Harvard：https://techcrunch.com/podcast/etched-founder-gavin-uberti-thinks-his-company-stands-on-the-shoulders-of-giants/ to launch Etched, not knowing then how to raise cash (much less the loads of it they would need) or how to hire.

“We had no idea how hard it was going to be,” Wachen says. “I think we still have to be humbled by what it will take to actually get to scale.”

Wachen remembers landing in the Bay Area after telling his parents he was leaving school to do a startup, with no office or apartment arranged. He slept on the floor of a friend’s unfurnished house.

“I remember staying in my friend’s house that they were about to sell, using a towel as a blanket,” he laughs. The founders eventually set up the servers they needed to run the chip-design tools in the garage of an early employee and “every time it needed to be rebooted, he would call his wife, and she would go and hit the reboot button.”

Today, there are 400 people bustling in an office, and Etched operates a 2 megawatt data center there. And it just opened a new 80,000 square-foot, 10MW facility in Milpitas, down the road from its main San Jose office.

“We’re running tokens in our lab today, working with some of the largest AI companies in the world,” he says.

Wachen also has a blanket now, and a mattress “and a pillow even. Multiple pillows,” he jokes.

More importantly, he and his co-founders never let the doubters stop them. “It’s come a long way. It’s a very, very different world. But I think, when you really think something’s possible, and you just work at it for a long time, you can do it.”

Note: This story was updated to include a reference to the new 10MW facility.

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