Cerebras Systems joined the Unicorn Club on November 10, 2021, after raising a $250 million Series F funding round led by Alpha Wave Global. Headquartered in Sunnyvale, California, United States, Cerebras Systems builds advanced AI compute infrastructure and wafer-scale processors designed for large-scale model training: the company’s technology powers multi-lingual LLMs, healthcare chatbots, and custom enterprise AI models. Cerebras has raised $1.55 billion to date and employs 275 people (as of December 2022).
Keep reading to learn more about how Cerebras Systems is transforming AI infrastructure with its groundbreaking wafer-scale computing technology.
What Is Cerebras Systems and What Does It Do?
Founded in 2015, Cerebras Systems develops high-performance AI infrastructure solutions that enable faster and more efficient training of large-scale AI models. The company’s flagship innovation, the Wafer Scale Engine (WSE), is the world’s largest and most powerful AI processor, designed to reduce training time and cost drastically.
Cerebras offers customers comprehensive solutions for training foundational models, fine-tuning open-source architectures, and deploying domain-specific AI applications. Its platform supports sectors such as healthcare, scientific research, and enterprise automation, empowering organizations to train models that were previously computationally impossible.
How Much Funding Has Cerebras Systems Raised?
1. Series G
- Amount Raised: $1.1 billion
- Date: September 30, 2025
- Lead Investor: Fidelity Management & Research and Atreides Management
- Valuation: $8.1 billion
- Purpose: To scale AI infrastructure globally, accelerate development of next-generation wafer-scale systems, and expand into cloud-based AI compute services.
2. Series F
- Amount Raised: $250 million
- Date: November 10, 2021
- Lead Investor: Alpha Wave Global
- Valuation: $4 billion
- Purpose: To deploy Cerebras CS-2 systems worldwide, enhance model training efficiency, and expand enterprise partnerships.
3. Earlier Rounds
- Total Funding: $200 million (combined from Series A–E)
- Key Investors: Benchmark, Coatue, Altimeter Capital, Foundation Capital, VY Capital
- Purpose: To fund R&D of wafer-scale chips, build prototype hardware, and commercialize large-scale AI compute technology.
Total Funding Raised: $1.55 billion
Latest Funding Date: September 30, 2025
Latest Valuation: $8.1 billion
Employee Count: 275 (as of December 31, 2022)
Key Investors
1. Fidelity Management & Research
- Details: Global investment management firm leading the Series G round, known for backing late-stage technology and AI infrastructure companies.
- Focus Areas: AI, semiconductors, and advanced computing.
2. Atreides Management
- Details: Growth-focused investment firm co-leading the Series G round, investing in disruptive AI and computing startups.
- Focus Areas: Deep tech, AI infrastructure, and enterprise technology.
3. Alpha Wave Global
- Details: Lead investor in Series F, focusing on high-growth companies in frontier technologies and global infrastructure.
- Focus Areas: AI, semiconductors, and data infrastructure.
4. Benchmark & Coatue Management
- Details: Early investors supporting Cerebras since its inception, backing its vision to revolutionize high-performance computing.
- Focus Areas: Technology, AI hardware, and scalable infrastructure solutions.
Where Is Cerebras Systems’ Headquarters?
Cerebras Systems is headquartered in Sunnyvale, California, United States. From its headquarters, the company designs, manufactures, and optimizes wafer-scale processors and AI systems that power large-scale model training for enterprises, research institutions, and cloud providers.
What’s Next for Cerebras Systems?
Following its $1.1 billion Series G round, Cerebras Systems plans to expand production of its wafer-scale chips, strengthen partnerships in the AI research and enterprise sectors, and advance toward a potential IPO. The company aims to establish global data centers powered by its CS-series systems, enabling organizations to train and deploy next-generation AI models faster and more efficiently than ever before.
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