--- title: Euclyd Secures 230 Million Dollars in Series A Funding url: https://www.dataloco.com/en/euclyd-secures-230-million-dollars-in-series-a-funding published: 2026-09-17T17:21:41+00:00 language: en section: AI source: https://www.cnbeta.com.tw/articles/tech/1577998.htm organizations: Euclyd, Samsung, Nvidia, Somerset Capital Partners, EQT, Innovation Industries publisher: Dataloco --- # Euclyd Secures 230 Million Dollars in Series A Funding Euclyd, a Dutch artificial intelligence chip startup, has completed a Series A funding round valued at 230 million dollars. The company, which was established in 2024, received this capital to support its efforts to challenge the market position of Nvidia in the AI chip sector. The funding round was co-led by Samsung, Somerset Capital Partners, the Scaleup Europe Fund managed by EQT, and Innovation Industries. The startup is developing a chip system specifically designed for AI inference tasks. Rather than replicating the development path of Nvidia's graphics processing units, Euclyd is seeking different solutions at the chip architecture level. The design covers both processor and memory architecture, aiming to improve efficiency when running AI models through methods that differ from traditional graphics processing units. AI inference refers to the process where trained artificial intelligence models execute tasks in practical applications, such as answering user questions, generating images, or processing business requests using large language models. Nvidia currently holds a dominant position in this field. The company's graphics processing units, originally designed for the gaming market, became the core hardware for training and running AI models due to their highly parallel computing architecture. This led to the creation of a vast software ecosystem. Many AI companies and cloud computing firms rely on Nvidia's hardware to run their services, which is a key reason the company has become one of the highest-valued technology firms globally. Euclyd plans to enter this market using a different architecture. The company intends to sell its own AI hardware and complete rack systems. Additionally, it plans to license its intellectual property, allowing other businesses to design their own chips using Euclyd's technology. This business model positions the company not only as a chip supplier but also as a provider of AI chip architecture and technology licensing. The participation of Samsung in this funding round is particularly notable. Samsung possesses a complete industrial chain ranging from semiconductor design and wafer manufacturing to memory chips and electronic products. Investing in a company that challenges Nvidia may have financial significance and could provide a foundation for future cooperation between the two firms in AI computing, storage, and advanced semiconductor technology. The large scale of this funding, achieved in a company that is only about two years old, reflects the high level of attention investors are paying to the AI inference chip market. As generative AI moves from the model training phase into large-scale commercial deployment, the number of inference tasks that data centers must process is increasing. Consequently, chip energy efficiency, memory bandwidth, and overall computing costs are becoming increasingly important factors. For AI data center operators, continuing to purchase large quantities of Nvidia graphics processing units provides access to a mature software ecosystem and strong computing performance. However, this also means facing very high hardware, power, and infrastructure costs. As a result, more cloud service providers, large technology companies, and AI firms are beginning to look for alternatives to Nvidia. This trend creates market entry opportunities for Euclyd, AMD, and other AI accelerator startups. Challenging Nvidia is not simply a matter of manufacturing a high-performance AI chip. The company's strength lies not only in its hardware but also in its software platform, development tools, drivers, and the developer ecosystem accumulated over many years. Any competitor hoping to replace Nvidia in large-scale data center environments must address issues such as software compatibility, developer migration costs, and long-term customer deployment risks. Euclyd is still in a relatively early stage of development. The primary significance of this funding is to provide sufficient capital for the company to continue chip research and development, refine its products, and build a commercial ecosystem. Whether the company can achieve clear performance and energy efficiency advantages in actual AI inference tasks using its different processor and memory architecture remains to be verified once its products enter the market. As demand for AI inference continues to grow, Nvidia is facing increasing competition from various directions. Euclyd has chosen to focus on architecture innovation and memory design, while other companies may seek breakthroughs through dedicated accelerators, custom application-specific integrated circuits, optical computing, and advanced packaging. The future AI chip market is likely to involve comprehensive competition around computing architecture, memory, software ecosystems, energy consumption, and overall system costs, rather than being a simple competition between graphics processing units. ## This story in other languages - [Français](https://www.dataloco.com/fr/euclyd-une-start-up-neerlandaise-de-puces-ia-leve-230-millions-de-dollars)