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About the application:

Face Recognition, Photo Classification, Text Completion... Is your phone capable of running the recent Deep Neural Networks to perform these AI-based tasks? Does it have a dedicated AI Chip? Is it quick enough? Run AI Benchmark to professionally evaluate its AI Performance! Current smartphone ranking: http://ai-benchmark.com/ranking.html AI Benchmark measures the speed, accuracy and memory requirements for a few key AI and Computer Vision algorithms. Among the inspected solutions are Photo Classification and Face Recognition ways, Neural Networks used for Photo Super-Resolution and Image Enhancement, AI models predicting text and performing Bokeh Result Rendering, as well as algorithms used in autonomous driving systems. The visualization of the algorithms’ outputs allows to assess their results graphically and to receive to know the current state-of-the-art in different AI fields. In total, AI Benchmark consists of 46 tests and 14 sections provided below: Section 1. Classification, MobileNet-V2 Section 2. Classification, Inception-V3 Section 3. Face Recognition, MobileNet-V3 Section 4. Parallel Model Execution, 8 x MobileNet-V2 Section 5. Optical Hero Recognition, CRNN Section 6. Image Deblurring, PyNET Section 7. Photo Super-Resolution, VGG19 Section 8. Photo Super-Resolution, SRGAN Section 9. Bokeh Result Rendering, U-Net Section 10. Semantic Segmentation, DeepLabV3+ Section 11. Parallel Segmentation, 2 x DeepLabV3+ Section 12. Photo Enhancement, DPED ResNet Section 13. Text Completion, LSTM Section 14. Memory Limits, SRCNN Besides that, one can load and try their own TensorFlow Lite deep learning model in the PRO Mode. A detailed description of the tests can be found here: http://ai-benchmark.com/tests.html Note: Hardware acceleration is supported on all mobile SoCs with dedicated NPUs and AI accelerators, including Qualcomm Snapdragon, HiSilicon Kirin, Samsung Exynos and MediaTek Helio / Dimensity chipsets. 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 needed).