Inside Agentic AI Workloads
Agentic workloads repeatedly re-enter model inference over growing state. We characterize how trajectories, KV-cache retention, and tool use shape serving demand.
Gimlet Labs Blog
A blog about our lab's research on high performance AI systems.
Previous Posts
Showing 5 previous posts tagged Announcement.
Scaling low-latency inference with Gimlet Cloud and Cerebras
Gimlet brings Cerebras’ wafer-scale compute into Gimlet Cloud, enabling inference at up to 3,000 tokens per second while expanding the performance and efficiency available for agentic and real-time AI applications.
Announcing Gimlet's Series B
Today, we are announcing our $300M Series B raise, 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 Venture Capital, and XTX Markets.
Building new benchmarks for the agentic era with MLCommons
Gimlet Labs is now a member of MLCommons, the nonprofit consortium behind MLPerf. Together, we'll help establish new open benchmarks for agentic inference.
Announcing Gimlet's Series A Raise
Today, we're announcing our $80M Series A raise, led by Menlo Ventures and joined by Eclipse, Factory, Prosperity7, and Triatomic.
Introducing Gimlet Labs: AI Infrastructure for the Agentic Era
We're excited to finally share what we've been building at Gimlet Labs. Our mission is to make AI workloads 10X more efficient by expanding the pool of usable compute and improving how it's orchestrated.