SAN FRANCISCO, June 29, 2026 (GLOBE NEWSWIRE) — Gimlet Labs, the Applied AI research and product company, today announced that it has joined MLCommons®. This AI industry engineering consortium delivers open, useful measures of quality, performance and safety to help guide responsible AI development. As part of the consortium, Gimlet Labs will contribute to new benchmarks for agentic inference and support open standards for ML performance across industry and research.
MLCommons develops MLPerf®, the industry-standard benchmark suite, which is defined by a working group of experts who establish fair, peer-reviewed benchmarks for AI systems. The working group defines the AI model to run, the data set against which it is evaluated, sets rules on what changes to the model are allowed and measures how fast a given piece of hardware runs the model. By working within this AI model tripod, the MLPerf benchmarks measure and improve AI performance in an open, repeatable and vendor-agnostic way.
“Gimlet Labs is doing something truly transformative with their multi-silicon approach for faster and more efficient inference. Because they orchestrate AI workloads across diverse hardware, the Gimlet Labs team has an invaluable perspective on agentic inference and what it needs from hardware. We’re thrilled to welcome them officially to MLCommons and to help us accelerate progress in inference performance,” said David Kanter, founder of MLCommons and head of MLPerf.
“The industry is moving away from homogeneous infrastructure and toward heterogeneous systems that target each phase of inference to the best hardware as agentic inference becomes the dominant software workload. We’re collaborating with MLCommons on a new set of benchmarks that reflect these growing workloads and the unique infrastructure that powers them,” said Zain Asgar, co-founder and CEO of Gimlet Labs.
To read Gimlet Labs’ blog on joining MLCommons as a member organization, go to: https://gimletlabs.ai/blog/announcing-mlcommons-membership.
About Gimlet Labs
Gimlet Labs’ mission is to drive breakthrough improvements in AI performance that result in massive increases in compute available for AI workloads. Gimlet Labs’ inference cloud is derived from its foundational research across the stack to enable the next generation of performant, scalable AI infrastructure. Its research combines theory and practice to push the boundaries of AI efficiency via techniques such as automated GPU kernel generation, workload orchestration and heterogeneous execution across diverse hardware. For more information, simply visit: https://gimletlabs.ai/.
About MLCommons
MLCommons is the world’s leader in AI benchmarking. An open engineering consortium supported by more than 125 members and affiliates, MLCommons has a proven record of bringing together academia, industry and civil society to measure and improve AI. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled into a set of industry metrics for measuring machine learning performance and promoting transparency in machine learning techniques. Since then, MLCommons has continued to use collective engineering to build the benchmarks and metrics required for better AI – ultimately helping to evaluate and improve the accuracy, safety, speed and efficiency of AI technologies. For more information, go to: https://mlcommons.org/.
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