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Gimlet Labs

Serverless AI inference platform with orchestration

Overview

Gimlet Labs builds an inference cloud platform that runs and coordinates AI agent workloads across heterogeneous hardware, including GPUs and accelerators. It splits workloads and routes tasks to the most suitable hardware to boost throughput without extra cost or power, and offers serverless inference in Gimlet Cloud to let developers scale multi-agent systems while the platform handles scheduling. The company also develops kforge, a toolkit that uses AI agents to automatically generate optimized PyTorch kernels for CUDA, ROCm, and Metal. Its goal is to make AI inference scalable and efficient by hardware-aware orchestration, with options to run in the cloud or on customers' data centers.

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About Gimlet Labs

Simplify's Rating
Why Gimlet Labs is rated
B
Rated B on Competitive Edge
Rated A on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsHardwareEnterprise SoftwareAI & Machine Learning

Company Size

51-200

Company Stage

Series B

Total Funding

$392M

Headquarters

San Francisco, California

Founded

2023

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Simplify's Take

What believers are saying

  • September 2026 Series B raised $300 million at a $3 billion valuation.
  • Cerebras partnership targets 100 megawatts and 3,000 tokens per second, with private deployments.
  • Gimlet said March 2026 customers tripled, adding a top-three frontier lab and hyperscaler.

What critics are saying

  • Gimlet depends on Cerebras CS-4 deliveries over 2026-2027 for promised capacity.
  • That $3 billion valuation demands rapid revenue conversion before rivals bundle heterogeneous inference.
  • If hyperscalers internalize multi-chip orchestration, Gimlet becomes a feature, not a company.

What makes Gimlet Labs unique

  • Gimlet's multi-silicon cloud routes each inference phase to GPUs, Cerebras, CPUs, and accelerators.
  • The software-first orchestration layer differentiates from single-chip peers like Groq and Cerebras.
  • Founders from Pixie and Stanford ship research-derived systems, including kforge kernel generation.

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Funding

Total Funding

$392M

Above

Industry Average

Funded Over

3 Rounds

Series B funding is typically for startups that have proven their business model and need more funding to expand rapidly—often by entering new markets or adding more products. Investors are usually venture capital firms that specialize in later-stage investments.
Series B Funding Comparison
Above Average

Industry standards

$35M
$45M
$65M
$100M
$300M

Benefits

Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

-15%

1 year growth

-11%

2 year growth

-14%
Data Center Dynamics
Sep 30th, 2026
Gimlet Cloud partners with Cerebras to deploy 100MW of wafer-scale compute.

Gimlet Cloud partners with Cerebras to deploy 100MW of wafer-scale compute. AI cloud startup recently secured $300 million in Series B funding round September 30, 2026 AI cloud startup Gimlet Cloud is partnering with wafer-scale chip and cloud company Cerebras. The two companies together will deploy 100MW of Cerebras' wafer-scale compute for inference workloads on Gimlet Cloud. The first data center under the agreement is expected to come online later this year. In addition, Gimlet will serve as one of the launch partners for Cerebras' upcoming generation of hardware, the CS-4, with availability for Gimlet customers in 2027. Gimlet Cloud is developing a cloud platform that offers a variety of silicon solutions, with the company noting in a blog post announcing the Cerebras partnership: "GPUs and wafer-scale systems have different strengths. The opportunity is to combine them within a single inference workload, using GPUs and Cerebras wafer-scale systems where each performs best, and in the process maximize both throughput and latency." This comes just weeks after Gimlet announced a $300 million Series B funding round, led by Andreessen Horowitz and joined by Sapphire Ventures, Menlo Ventures, 645 Ventures, Arm, Eclipse, Emergence, Factory, Hudson River Trading, M12, OnePrime Capital, Prosperity7, QuantumLight, Samsung Ventures, Tiger Global Management, Triatomic, Wing Ventures, and XTX Markets. This gave the company a valuation of $3 billion. CEO Zain Asgar said at the time of the Series B funding round: "Since March, we've secured billions of dollars in contracted revenue and are scaling toward hundreds of megawatts of managed capacity. This funding will help us build that infrastructure, expand our team, and bring high-performance inference to many more customers." A Series A round was held in March and raised $80 million. Gimlet is based in San Francisco and was founded by Zain Asgar, Michelle Nguyen, Omid Azizi, Natalie Serrino, and James Bartlett. Asgar is also a professor of computer science at Stanford University. Details about the company's data center footprint have not been provided. The company is currently hiring for a data center facilities operations lead. More in Cloud & hyperscale.

Yahoo Finance
Sep 28th, 2026
Gimlet Labs partners with Cerebras to deliver AI inference speeds up to 3,000 tokens per second

Gimlet Labs and Cerebras Systems announced a collaboration to deliver ultrafast AI inference through Gimlet Cloud. The partnership combines Cerebras' wafer-scale compute with Gimlet's inference technology to achieve speeds of up to 3,000 tokens per second for real-time AI applications. Gimlet Cloud integrates the Cerebras Wafer Scale Engine with GPUs, using advanced disaggregation technology to optimise each phase of inference. The first Cerebras-powered Gimlet Cloud datacentre is expected to launch later this year. The collaboration aims to improve user experience in real-time AI applications such as voice assistants and AI agents, where reduced latency creates more responsive interactions. Gimlet Labs will serve as a launch partner for Cerebras' CS-4 technology, providing developers with production-scale access to the combined infrastructure.

AiThority
Sep 28th, 2026
Gimlet Labs adds Cerebras to deliver ultrafast AI inference through Gimlet Cloud.

Gimlet Labs adds Cerebras to deliver ultrafast AI inference through Gimlet Cloud. Deployment combines Cerebras wafer-scale compute with Gimlet's inference Cloud to deliver up to 3,000 tokens per second. Gimlet Labs and Cerebras Systems (NASDAQ: CBRS) today announced a collaboration to deliver a new class of ultrafast AI inference at massive scale. The collaboration brings together Cerebras' wafer-scale compute with the Gimlet Cloud to deliver a purpose-built disaggregated inference cloud spanning datacenter infrastructure to developer APIs. Together, the companies plan to deliver speeds of up to 3,000 tokens per second for demanding agentic and real-time applications, with the first Cerebras-powered Gimlet Cloud datacenter expected to come online later this year. In AI, speed drives user experience and engagement and shapes what users can build. For real-time applications, from voice and video AI to agents and assistants, latency can be the difference between an interaction that feels seamless and one that feels slow. Real-time AI feels like an active collaborator that is immediate, fluid and responsive. When AI responds in real time, users do more with it, stay longer and run higher value workloads. As a result, fast tokens are more valuable tokens. Gimlet Cloud combines the Cerebras Wafer Scale Engine with GPUs into an integrated inference solution. It uses advanced inference disaggregation technology to orchestrate model execution so each phase of inference runs on the silicon best suited to it. Together, these capabilities deliver a new class of fast inference optimized for production-scale agentic and real-time workloads. Sep 28, 2026 Prev Next 1 of 43,702 "Inference speed matters. It determines how productive AI can be. Fast inference creates magical user experiences and opens new markets. By combining Gimlet's multi-silicon software with the Cerebras Wafer Scale Engine, we can run each phase of inference on the hardware best suited to it and plan to deliver up to 3,000 tokens per second at production scale," said Zain Asgar, co-founder and CEO of Gimlet Labs. "Combining the fastest tokens from Cerebras with the highest throughput GPUs delivers the best datacenter economics for everyone," said Sean Lie, co-founder and CTO at Cerebras. "Everyone wants more high value tokens. Cerebras delivers the fastest AI inference in the world, and GPUs deliver high throughput. By making Cerebras a native part of its inference cloud, Gimlet will bring our industry leading speed and intelligent AI to more developers at production scale. We're excited to build with Gimlet as a launch partner for CS-4, giving customers a direct path to our latest technology." The collaboration builds on joint customer engagements underway since last year and an integrated solution already serving tokens in private deployments. Gimlet Labs will expand the collaboration with Cerebras to integrate software, infrastructure design, APIs, developer tooling, optimization, validation and production operations to make ultrafast inference broadly available through Gimlet Cloud.

Channel NewsAsia
Sep 28th, 2026
Cerebras to supply AI systems to cloud computing startup Gimlet Labs.

Cerebras to supply AI systems to cloud computing startup Gimlet Labs. 28 Sep 2026 09:06PM Add CNA as a trusted source to help Google better understand and surface our content in search results. SAN FRANCISCO, Sept 28: Cerebras Systems plans to supply AI chips and hardware with capacity to consume roughly 100 megawatts to startup Gimlet Labs to help run its cloud computing business, the companies said on Monday. The deal between Gimlet and Cerebras is part of rising interest from AI companies in procuring hardware that is capable of speedy AI calculations known as inference, the process in which a chatbot such as Anthropic's Claude generates a response to a user question. Performing inference operations speedily can help in areas such as cybersecurity, voice applications and financial analysis, Gimlet CEO Zain Asgar said in an interview with Reuters. For this hardware, Gimlet plans to target selling to companies and startups that are building their entire products around AI in some way, Asgar said. Gimlet plans to use the Cerebras hardware to run so-called frontier models - the cutting-edge AI models - that require enormous amounts of computing power to run speedily. Cerebras plans to supply its CS-4 systems, which it unveiled over the summer, over one to two years, its CEO, Andrew Feldman, said. Gimlet plans to make the CS-4 hardware available in its cloud in 2027, the company said. The deal is "further validation from Cerebras... of how easy it is to deploy, even in heterogeneous environments," Feldman said, referring to installing the hardware alongside chips and systems from other companies. Cerebras and Gimlet declined to disclose the financial terms of the deal. Gimlet will be responsible for maintaining and operating the systems once delivered by Cerebras. OpenAI and companies such as Nvidia have recognized the importance of the ability to perform speedy inference. Earlier this year, Cerebras signed a deal to supply OpenAI with chips. And last year, Nvidia signed a licensing deal with Groq for the company's chips and hardware.

HYPERURANIOS
Sep 7th, 2026
2026 funding rounds across biotech, AI and robotics sectors.

2026 funding rounds across biotech, AI and robotics sectors. A roundup of major financing events in biotechnology, artificial intelligence and robotics reported in 2026. Compiled automatically from the sources listed below and checked against Hyperuranios' own capital and research data. Every figure here traces to a linked source. Factual errors reported to the contact address are corrected in the article and noted here. Artificial intelligence. Gimlet Labs announced a $300 million Series B round that lifted its post-money valuation to $3 billion, led by Andreessen Horowitz with participation from Sapphire Ventures, M12, Arm, Menlo Ventures and Factory; the capital will fund expansion of its heterogeneous inference cloud that matches AI workloads to the optimal silicon, a strategy the company says will improve throughput and power efficiency for agentic AI models [2]. San Mateo-based XDOF is in late-stage talks for a Series B valued at roughly $1.2 billion, reportedly led by 8VC, after closing a $70 million Series A three months earlier backed by Thrive Capital, Andreessen Horowitz, Lux Capital, Spark Capital and WndrCo; the startup builds data-pipeline and teleoperation tools that generate physical-world training data for general-purpose robots, a capability it says underpins its rapidly growing $50 million-annual revenue business [4]. An analysis of 2026 venture activity notes that headline-grabbing megarounds in artificial-intelligence firms are inflating overall funding statistics, with North-American AI companies alone accounting for the bulk of the $392 billion reported in the first half of the year, while non-AI startups face a markedly tighter capital environment [6]. Kuwait-based EdTech startup Dawraty raised a $2 million seed round led by Qatar Development Bank to scale its AI-powered bilingual medical-education platform, expand operations in Qatar and deepen commercial partnerships such as a reseller agreement with the Qatar Finance and Business Academy [8]. Italian AI company Cato secured €6 million in a seed round led by Keen Venture Partners, with participation from Vento, Heartfelt, Moonstone, BHeroes, Alecla7, Nova Venture and several angel investors, to further develop its automated public-tender platform, grow its team and extend its services internationally [9]. Robotics. Jaipur Robotics closed a €4.3 million seed round co-led by EquityPitcher Ventures and High-Tech Gründerfonds, with earlier backing from Fondazione Acire, to accelerate international expansion, deepen its computer-vision AI platform for waste-to-energy, cement and biomass plants, and broaden product depth; the company reports hazard-detection accuracy of 99 % and claims over €1 million annual value from improved waste mixing [1][3]. French-based Lupin Dental completed a €15 million Series A for its supervised robotic system that automates minimally invasive tooth preparation for aesthetic veneers; the round was led by Fynveur with a €10 million investment and included Bpifrance and existing shareholders, and the funds will be used to expand partnerships with dental institutions and pursue broader commercial adoption after receiving UKCA certification [5]. Robotics venture capital in 2026 has approached $23 billion, with humanoid-specific funding exceeding $8.6 billion, illustrated by large checks such as Figure AI's $2.34 billion at a $39 billion valuation, Neura Robotics' up-to-$1.4 billion round backed by Nvidia, Amazon, Bosch and Schaeffler, and Apptronik's Series A exceeding $935 million, underscoring a software-style valuation approach to hardware-intensive humanoid firms [7].

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