Sparxity Joins Silicon Catalyst and Closes Series A, Bringing Total Funding to $90 Million

Formerly known as SpiNNcloud, Sparxity is developing energy-efficient AI chips that target up to 44x faster responses for certain models.

DRESDEN, GERMANY & SILICON VALLEY, November 11, 2026 - Silicon Catalyst today welcomed Sparxity (formerly known as SpiNNcloud) as a new Portfolio Company. Sparxity designs AI computing systems, from chips to software, that skip unnecessary calculations to improve speed and energy efficiency.

Sparxity’s Series A brings its team’s total funding to $90 million. ICM HPQC Fund led the round, joined by investors such as Lockheed Martin Ventures, GlobalFoundries, GS Futures, Cloudberry Ventures, TGFS and the EIC Fund. Angel investors Richard Socher and Nancy Xu, both named to the TIME100 AI list, also took part, alongside continued support from Atlantic and Silicon Catalyst.

“Silicon Catalyst exists to help semiconductor startups turn breakthrough ideas into products the world needs, and few needs are more pressing than making AI more energy efficient,” said Pete Rodriguez, CEO of Silicon Catalyst. “Sparxity pairs real commercial traction with a genuinely new approach to AI hardware. We’re excited to welcome them to our Portfolio and to help them scale.”

Helping AI Do Less Work for Each Answer

Many AI models perform calculations using nearly all their parts at each step, even when only a small portion is relevant. Sparxity’s systems support models that activate only the parts they need, reducing calculations and data movement. Its next-generation chips target up to 44 times faster responses for certain models.

"The next era of AI will be defined not just by how much computing power we can deliver, but by how intelligently and efficiently we use it," said Sparxity co-founder and CEO Hector Gonzalez. "This financing is a powerful validation of our vision for sparse-native computing and the complementary positioning of our systems. With the backing of leading, strategic investors, we're accelerating the transition from dense, energy-intensive architectures to heterogeneous datacenters with dedicated silicon for ultra-sparse workloads to unlock greater AI performance and lower costs."

Proven Technology, Growing Fast

On selected HPC and AI workloads, Sparxity reports:

  • 10 times faster sparse solvers

  • 18 times less energy use for event-driven machine learning

  • 20 times shorter run times for optimization problems

Sparxity quadrupled revenue from 2024 to 2025, with continued momentum in 2026. The team has completed three tapeouts, produced more than 70,000 chips and deployed 12 server racks. Its more than 30 customers include some of the world’s largest supercomputing facilities.

Deployments and Data Center Partnerships

Sparxity recently announced a multimillion-dollar deployment of its system at Germany’s Jülich Supercomputing Centre, part of Forschungszentrum Jülich. At the Centre, Sparxity’s technology supports machine learning and large-scale scientific computing. The company has also partnered with Deutsche Telekom to bring its technology to T-Systems’ data centers, with the goal of building energy-efficient AI computing infrastructure across Europe.

About Sparxity

Sparxity builds sparse-native compute for AI. Their principle is simple: compute only what matters. For years, models have been shaped by the dense hardware they run on. Sparxity builds the hardware that lets them go further: full-stack systems, from custom chips to software, built for fine-grained, dynamic sparsity, where intelligence scales without trading off speed or efficiency. Deployed in rack- and supercomputer-scale systems across Europe and the US, Sparxity opens a new world of compute for the builders shaping what comes next. Learn more at sparxity.ai.