All benchmark ai smartphone4/9/2023 ![]() Starting from AI Benchmark v4, one can also enable GPU-based AI acceleration on older devices in the settings ("Accelerate" -> "Enable GPU Acceleration", OpenGL ES-3.0+ is required). Note: Hardware acceleration is supported on all mobile SoCs with dedicated NPUs and AI accelerators, including Qualcomm Snapdragon, HiSilicon Kirin, Samsung Exynos, MediaTek Helio / Dimensity and UNISOC Tiger chipsets. Question Answering, MobileBERTīesides that, one can load and test their own TensorFlow Lite deep learning models in the PRO Mode.Ī detailed description of the tests can be found here: Parallel Model Execution, 8 x Inception-V3 In total, AI Benchmark consists of 78 tests and 26 sections listed below: The visualization of the algorithms’ outputs allows to assess their results graphically and to get to know the current state-of-the-art in various AI fields. Among the tested solutions are Image Classification and Face Recognition methods, Neural Networks used for Image / Video Super-Resolution and Photo Enhancement, AI models predicting text and performing question answering, as well as AI solutions used in autonomous driving systems and smartphones for real-time Depth Estimation and Semantic Image Segmentation. ![]() Is your smartphone capable of running the latest Deep Neural Networks to perform these and many other AI-based tasks? Does it have a dedicated AI Chip? Is it fast enough? Run AI Benchmark to professionally evaluate its AI Performance!ĪI Benchmark measures the speed, accuracy, power consumption and memory requirements for several key AI and Computer Vision algorithms. Still, smartphone shipments were at least 5 below a previous forecast. Face Recognition, Image Classification, Question Answering. Nvidia said its A100 GPUs won all the MLPerf benchmark tests for AI inference.
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