Gimlet Labs Raises $80M Series A to Solve AI’s Chip Efficiency Problem

Quick Facts

Gimlet Labs raised $80 million Series A led by Menlo Ventures, bringing total funding to $92 million
Company claims its multi-silicon platform speeds up AI inference workloads 3-10x for the same cost and power
Customer base has tripled since public launch in October 2025, including top frontier labs and hyperscalers

Gimlet Labs closed an $80 million Series A round led by Menlo Ventures to address what the company calls one of AI’s biggest bottlenecks: massive hardware underutilization in data centers.

The startup’s multi-silicon inference cloud platform splits AI tasks across different types of processors simultaneously. Current hardware sits idle 70-85% of the time, according to CEO Zain Asgar.

“Apps are only using the existing hardware already deployed somewhere between 15 to 30 percent of the time,” Asgar said. “You’re wasting hundreds of billions of dollars because you’re just leaving idle resources.”

Gimlet partners with chip makers including NVIDIA, AMD, Intel, ARM, Cerebras and d-Matrix. The platform can slice AI models so different parts run on different processors – compute-intensive batch inference uses GPUs, latency-sensitive workloads run on specialized SRAM-heavy processors, and orchestration tasks use CPUs.

The company launched publicly in October 2025 with eight-figure revenues. Its customer base has more than doubled in four months and now includes one of the top three frontier labs and one of the top three hyperscalers.

Market Opportunity

The global AI inference market was valued at $103.73 billion in 2025 and is projected to reach $312.64 billion by 2034. Inference workloads will account for roughly two-thirds of all compute by 2026, up from one-third in 2023.

McKinsey estimates data center spending will reach nearly $7 trillion by 2030 if current deploy-more-compute trends continue. Gimlet’s approach targets this inefficiency by maximizing existing hardware utilization.

“Heterogeneity is inevitable, and Gimlet Labs is ahead of it,” said Tim Tully, partner at Menlo Ventures. “Most infrastructure was built for a homogeneous world – and the industry is paying hundreds of billions in CapEx for it.”

Team and Background

Asgar previously co-founded Pixie Labs, which was acquired by New Relic in 2020. He worked as a GPU architect at NVIDIA and engineering lead at Google AI. Co-founders Michelle Nguyen, Omid Azizi, and Natalie Serrino also came from Pixie.

The 30-person company will use the funding to expand its team and scale its inference cloud. Eclipse Ventures, Prosperity7 and Triatomic also participated in the round, along with angels including Sequoia’s Bill Coughran and Intel CEO Lip-Bu Tan.

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