<p><strong>SAN FRANCISCO</strong> &#8212; Gimlet Labs, an Applied AI research and product company, has raised $300 million in Series B funding, bringing its current valuation to $3 billion and the total funding raised to $392 million. This round was led by Andreessen Horowitz with participation from major investor Sapphire Ventures, other new investors M12 and Arm and previous investors Menlo Ventures and Factory.</p>
<p>“AI demand is growing exponentially, while data centers and silicon can’t keep pace. The answer isn’t just more infrastructure &#8211; it’s a better architecture. Gimlet has built a new kind of inference cloud, heterogeneous by design, that matches each workload to the right silicon. By making GPUs and purpose-built accelerators work as one system, Gimlet delivers dramatically more throughput, more interactivity and more intelligence from every watt. We believe this is where inference infrastructure is headed,” said Raghu Raghuram, managing partner at Andreessen Horowitz and Gimlet Labs board member.</p>
<p>The explosion of agentic workloads has exposed a critical limitation in today’s AI infrastructure: homogeneous hardware alone cannot meet the speed and efficiency needs of agentic workloads. With inference now reaching quadrillions of tokens per month, and still growing, the one-size-fits-all approach leaves massive inefficiencies in performance and utilization, even as the industry gears up to spend an estimated $765 billion in AI CapEx this year, with 7.6 trillion in cumulative spending from 2026-2031, according to Goldman Sachs.*</p>
<p>In October 2025, Gimlet Labs emerged from stealth to solve this problem with the industry&#8217;s first multi-silicon inference software designed for faster, more interactive agentic AI workloads. Gimlet disaggregates AI models to run each phase of inference on the most appropriate silicon, improving both inference latency and throughput, and is available through its own managed cloud or as a managed service in customer environments. Gimlet Labs works with leading AI chip companies, including NVIDIA, AMD, Intel, Arm, Cerebras and d-Matrix to support their chips in its multi-silicon architecture.</p>
<p>In March 2026, Gimlet Labs announced that it tripled its customer base and added one of the top three frontier labs as well as one of the top three hyperscalers as customers.</p>
<p>Since then, Gimlet Labs has secured billions of dollars in contracted revenue for Gimlet Cloud and is scaling to hundreds of megawatts in managed heterogeneous infrastructure. The new capital will be used to build out operations for its multi-silicon cloud as well as to continue to expand its team.</p>
<p>“We’ve reached a turning point where inference is the dominant AI workload and the demand for tokens is explosive. With Gimlet, our customers are able to serve massive volumes of tokens at very low latency, even as their AI workloads continue to grow across all dimensions. We’re able to deliver unprecedented performance because Gimlet software intelligently slices and orchestrates their workloads across different types of hardware from both mainstream and emerging chipmakers,” said Zain Asgar, co-founder and CEO of Gimlet Labs.</p>
<p>Gimlet says it is the only AI cloud built with multi-silicon inference software and heterogeneous infrastructure and combines:</p>
<ul >
<li>Multi-silicon datacenters that integrate GPUs, purpose-built AI accelerators including SRAM-based architectures and CPUs, in one coherent solution</li>
<li>Inference software that disaggregates AI workloads, matching each phase of the workload to its optimized hardware architecture, achieving up to 10X gains in throughput and interactivity</li>
<li>Intelligent orchestration of AI workloads across compute nodes</li>
</ul>

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