Nvidia-backed SiFive raises $400M at $3.65B valuation for open-source AI chips
NVIDIA-backed SiFive raised $400 million at a $3.65 billion valuation to accelerate its open-source RISC-V chip designs for AI data centers, positioning itself as an alternative to proprietary x86 and ARM architectures in the data center solutions market.
SiFive, the company founded by UC Berkeley engineers who created the RISC-V open-source chip architecture, announced on Thursday that it closed an oversubscribed $400 million Series G round at a $3.65 billion valuation. The round will fuel SiFive's expansion into data center solutions based on open standards. In January, SiFive announced that it would adopt and integrate NVIDIA NVLink Fusion; as a result, its hardware solutions can now connect directly to NVIDIA GPUs and accelerators.
The round was led by Atreides Management, with participation from Apollo Global Management, Nvidia, Point72 Turion, T. Rowe Price, and returning investors Prosperity7 Ventures and Sutter Hill Ventures. This is SiFive's first raise since March 2022, when it secured $175 million at a $2.33 billion valuation.
Unlike traditional x86 and ARM processors, SiFive licenses open-standard RISC-V chip designs that companies can customize for their needs. The company is now pivoting from embedded systems to high-performance data center CPUs, targeting what it calls the "agentic AI" opportunity. According to the company, SiFive's strategic expansion towards data center solutions responds to the demands of hyperscaler customers, who are reportedly looking for open standard data center alternatives that are highly customizable and do not lock them into a specific vendor's ecosystem
"As AI evolves toward more complex agentic models, efficient CPU performance is critical," said CEO Patrick Little. SiFive expects that integrating with Nvidia's CUDA software and NVLink Fusion infrastructure will position the company to capture part of what analysts estimate could be a $100 billion-plus market.
Ellie Ramirez-Camara is the News Editor at Data Phoenix, where she writes the daily AI newsdesk — covering model releases, research, funding rounds, and policy across the AI and machine-learning industry. She tracks announcements from labs and startups alike and distills them into clear, source-linked reporting for practitioners.
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