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Nvidia backs SiFive as it hits $3.6b valuation

SiFive of Santa Clara said it raised US$400 million in a series G round led by Atreides Management to expand its RISC-V data center CPU and AI IP solutions.

The chip IP company was valued at US$3.65 billion and said Apollo Global Management, Nvidia, Point72 Turion, T. Rowe Price Investment Management, Prosperity7 Ventures, and Sutter Hill Ventures also joined the round.

SiFive said the money will fund R&D on CPU and accelerator IP, software work building on existing ports of CUDA, Red Hat, and Ubuntu, and customer deployment efforts including Nvidia NVLink Fusion.

The company cited demand from AI data center customers for customizable CPU designs but provided no revenue figures, customer names, or deployment timelines in the announcement.

🔗 Source: SiFive

🧠 Food for thought

Implications, context, and why it matters.

Funding ties to a specific chip and early customer use

  • SiFive’s 3rd generation Performance P870-D, built to compete with Arm’s Neoverse N2 class in the data center, is running in customer silicon 1.
  • A tier-1 hyperscaler (a very large cloud company) is profiling P870-D cores on video encoding, recommender systems, and big data analytics 2.
  • The same customer expects server-specific SoCs, or systems on a chip that combine multiple computing functions into one chip, based on this design in the second half of 2025 2.
  • SiFive said 2025 revenue hit a company record and grew more than 50% year over year 1.

Nvidia plans NVLink Fusion support for SiFive RISC-V platforms

  • Alongside the investment, SiFive says it is adopting Nvidia NVLink Fusion in its high-performance data center-class products 3.
  • The goal is coherent links between customizable RISC-V CPUs, Nvidia GPUs, and other accelerators for tightly integrated AI systems 3.
  • RVA23 ratification, a technical specification meant to improve software compatibility across RISC-V chips, has boosted ecosystem support. That includes Nvidia’s CUDA porting announcement with no timeline disclosed, plus major Linux distribution work 4.
  • Nvidia’s support for a customizable, open-standard architecture gives hyperscalers a path to more power-efficient specialized AI systems beyond the usual server CPU market led by a handful of vendors 5.

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