Liquid AI Open-Sources Pipette: A Reproducible Benchmarking Suite That Measures On-Device Models, Quantization, Runtime and Hardware Together
Model cards lie. Liquid AI just open-sourced Pipette to measure what actually happens on your phone.
Why it matters
On-device model performance diverges sharply from server benchmarks—quantization, runtime, and hardware interactions create real-world gaps that model cards ignore. Pipette fills that measurement void with reproducible edge-device evals, addressing a blind spot practitioners face when deploying to phones and embedded systems.
The key facts
5 to knowLiquid AI released Pipette, open-source benchmarking suite for edge-device models
Partnership with Artificial Analysis for independent methodology validation
Benchmarks measure on-device behavior under quantization, runtime, and hardware variation
Addresses gap between server-class full-precision model cards and actual phone performance
Treats on-device behavior as first-class measurement concern, not afterthought
Go to the source
MarkTechPostmarktechpost.com
Publisher excerpt: Model cards report quality under server-class, full-precision conditions. Those numbers rarely predict how the same model behaves on a phone. This week, Liquid AI released Pipette. It is an open-source platform for benchmarking foundation models on edge devices, built in partnership with Artificial…