Nvidia rivals eye huge funding rounds as AI chip market booms
European chip startups develop alternative technology Nvidia’s Graphics processing units (GPUs) are eyeing major funding rounds as they try to scale amid the AI boom.
Dutch company Euclyd is backed by the chipmaking equipment giant’s former CEO ASMLThe company is currently in talks with investors for a round of at least 100 million euros ($118 million), founder Bernardo Kastrup told CNBC in an exclusive interview.
Elsewhere, UK startup Optalysys plans to raise more than $100 million towards the end of this year, and British company Fractile and France’s Arago have reportedly raised nine-figure rounds. Fractile declined to comment and Arago did not respond to a request for comment. Investors have poured more than $200 million into the Netherlands’ Axelera and the UK’s Olix so far in 2026.
Nvidia has quickly become the world’s most valuable company as its GPUs, originally designed for gaming, have been repurposed to train AI models, but eyes are now turning to the most efficient ways to use those models, known as AI inference.
While the US chip giant is developing semiconductor systems for this purpose, a number of new European startups are emerging that claim that the technology they produce can do this more efficiently.
“Inference is dominant right now, and the current GPU architecture is not built around it in the most significant way at scale,” Patrick Schneider-Sikorsky, director of the NATO Innovation Fund (NIF), which invested in Fractile, told CNBC.
“Geopolitical headwinds are clearly evident due to US export controls and concentration risk.” [chipmaker] TSMC and a truly European sovereign computing imperative is pushing capital towards domestic silicon.”
ASML graduates
Euclyd is developing AI chips that run on a system that Nvidia says can deliver 100 times higher power efficiency for inference compared to the latest generation of Vera Rubin chips. Nvidia did not respond to CNBC’s request for comment.
The Dutch startup, which was founded in 2024 by former ASML director Kastrup and counts former ASML CEO Peter Wennink as an advisor and investor, has already raised a seed round of under €10 million and is now seeking new funds to scale its technology and start supplying its first customers.
Kastrup said Euclyd is developing chip systems to replace GPUs, but with a different architecture. While GPUs spend time and energy moving data through the memory stack, Euclyd’s chips will process data in multiple places, which Kastrup says will increase the efficiency of AI inference.
He added that the company’s silicon systems for basic models will reduce the energy, cost and footprint of the AI data center infrastructure. But unlike Nvidia’s chips, Euclyd’s systems have yet to be proven to be deployed at scale with commercial partners.
Euclyd’s prototype system. Credit: Euclyd.
Euclyd is working on this. It has already developed a chip for AI inference and is currently developing a multi-chip system that will process faster than the current iteration of its product, which it aims to produce by 2028. Kastrup said the company is in talks with four potential customers and hopes to start supplying two of them next year and two more the year after.
Taavet Hinrikus, partner of Plural, one of the company’s investors, told CNBC that Olix, which develops photonics-based processors for artificial intelligence, is currently in the research and development phase, but is targeting first customers next year.
Photonic processors are systems on chips that use light to move data and, in some cases, perform calculations.
Hinrikus said the startup will target all customers who need inference services, including hyperscalers and governments. Olix did not respond to a request for comment.
Hinrikus said the electronic architecture of the chips, which include GPUs, is truly “breaking the limits” in terms of how small it can be made. Chip manufacturers are trying to make processors smaller so they can fit more components on wafers and improve the economics of running systems on them.
“Heat [current chips] Creating is becoming an important problem. “We strongly believe that photonics platforms will be the next paradigm,” he added.
Nvidia is also working hard to stay ahead of the pack. The chip giant spent more than $18 billion on research and development in its last fiscal year, which ended in January 2026. It purchased assets from the artificial intelligence extraction startup in December. It acquired Groq for $20 billion and in March announced a $4 billion investment in two companies developing photonics technology.
Challenges for European startups continue
European startups face obstacles.
“Chip development timelines are long, the distance from tape output to volume distribution is challenging, and Europe’s foundry ecosystem still needs to mature,” NIF’s Schneider-Sikorsky said.
Axelera CEO Fabrizio Del Maffeo told CNBC that governments in Europe are still “conservative” about investing in products from startups and don’t have the equivalent of DARPA, the U.S. Department of Defense research agency that funds startups and other technology projects.
He also added that Europe lacks mechanisms to encourage the consumption of locally produced products, and fragmented labor laws across borders make it difficult to recruit European talent.
European AI chip startups have lagged behind in funding, raising $800 million so far in 2026, compared to $4.7 billion from their U.S. counterparts, according to Dealroom.
In the US, Cerebras Systems raised $1 billion in February, and this year saw a $500 million round for MatX, Ayar Labs and Etched.
However, European startups developing chips for artificial intelligence inference to rival Nvidia are increasingly attracting investor attention.
“We see this in deal flow and in our conversations with founders in the space,” Carlos Espinal, managing partner of Seedcamp, which backs chip startup Vaire Computing, told CNBC. “This is no longer a private bet. It’s becoming a fundamental part of how people think about AI infrastructure.”
