Gimlet Labs Raises $300 Million at a $3 Billion Valuation

San Francisco-based Gimlet Labs has raised $300 million in a Series B led by Andreessen Horowitz, valuing the AI infrastructure startup at $3 billion just six months after its $80 million Series A. New investors Arm and M12, Microsoft's venture fund, joined a large existing syndicate that includes Sapphire Ventures, Menlo Ventures, Tiger Global, Samsung Ventures, and Eclipse, among others.

Splitting AI Workloads Across Multiple Kinds of Chips

Gimlet Labs builds what it describes as the industry's first multi-silicon inference cloud for agentic AI, technology that divides AI workloads across multiple different types of chips rather than routing everything through a single chip architecture. That approach targets a real, growing problem: as AI inference workloads scale, relying on just one chip type for every kind of task leaves meaningful performance and cost efficiency on the table.

A Six-Month Jump From $80 Million to $300 Million

Raising a $300 million Series B only six months after an $80 million Series A, at a valuation that reaches $3 billion, is an unusually fast progression even by the standards of this year's AI infrastructure funding market. The size and speed of the round, along with an investor syndicate spanning traditional venture firms, strategic chipmakers, and crossover growth funds, signals strong conviction that multi-silicon inference will become standard infrastructure as agentic AI workloads scale.

Strategic Chipmakers Betting on Neutral Infrastructure

Arm and Samsung Ventures joining the round alongside Microsoft's M12 is notable specifically because Gimlet Labs' entire pitch depends on remaining neutral across chip architectures rather than favoring any single manufacturer's silicon. A chipmaker investing in a company built to route workloads across multiple competing chip types, its own included, is a bet that owning a stake in the routing layer itself is more valuable than trying to lock customers into one architecture exclusively, a meaningfully different strategic posture than the vertically integrated approach most chip companies have historically taken.

What This Means for Founders

Gimlet Labs' round shows that investors continue to reward infrastructure startups solving a genuine technical bottleneck in AI deployment, chip-level workload allocation in this case, with both fast follow-on rounds and a broad syndicate spanning strategic and financial capital. AngelLinx's AI and machine learning investor directory helps founders identify investors active in AI infrastructure and chip-level optimization, and the fit-scoring match tool connects founders with the right match as technical differentiation becomes the core of their pitch. The live listings page shows current founder campaigns performing against real investor interest today, and AngelLinx's guide to managing burn rate is essential reading for founders running capital-intensive infrastructure development cycles. The AngelLinx newsroom tracks major AI infrastructure funding rounds as they develop. Founders building differentiated AI infrastructure can register at https://angellinx.ai/register today.

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