Today we release Pipette, a model evaluation suite for on-device intelligence, in partnership with @ArtificialAnlys Most benchmarking platforms are optimized to measure core capabilities and speed profile of foundation models served in the cloud. Pipette gives the field a common, reproducible way to measure the quality, speed, latency, and memory use of AI models on devices such as phones, laptops, PCs, AI boxes, and embedded hardware. > Pipette is open source > In Pipette, models get compated as model + quantization + runtime + device from one interface. > It comes with a warehouse of verified benchmark results, currently with 10k+ results across 35 model classes, 7 quants, llama.cpp runtimes, and 4 devices. > Pipette is a dynamic platform, allowing new contributions from day one, adding new devices, runtimes, model families, and quantization levels. 🧵