Geekbench google pixel 6 android#
Geekbench google pixel 6 software#
Geekbench google pixel 6 windows#

Geekbench google pixel 6 software#

Depth data for each point on the image in this type of workload is used by camera software effects to programmatically add enhancements like subject isolation, blur, and other effects, reflecting real-world ML applications. Our model generates an image which “maps” where each pixel corresponds to an estimate of depth for that location in the original image. The new Depth Estimation workload reflects the advancements made in AI-powered photography used in software-assisted portrait mode effects. To more accurately reflect the kinds of tasks performed by your apps and software, Geekbench ML 0.6 includes three entirely new workloads. These changes together better illuminate real-world AI machine learning and performance on your device. On iOS, for example, the switch to Core ML better reflects modern app use cases, as developers targeting the platform are less likely to use TensorFlow Lite. And on iOS and macOS, Geekbench ML 0.6 uses Core ML directly, executing models with the CPU, GPU, or Neural Engine.Īll this combines to mean that Geekbench ML 0.6 uses newer, better frameworks that support more up-to-date models and faster performance on newer hardware. On Windows, we support ONNX with DirectML CPU and GPU support.

Geekbench google pixel 6 android#

Geekbench ML 0.6 upgrades our internal version of TensorFlow Lite, supporting newer models and improved performance on Android hardware with NPUs using NNAPI. New Frameworksĭevelopers don’t typically work directly on bare hardware in assembly - abstraction layers and frameworks simplify the process. And, as always, our models and data sets are identical across all supported platforms, making scores comparable. This means you’ll be able to see how machine learning-powered tasks run on your desktop, laptop, or even a server - whether it has new AI-specific hardware or not. With this latest 0.6 preview, Geekbench ML now supports Windows, macOS, and Linux.

Geekbench google pixel 6 windows#

New Platforms Geekbench ML on Windows 11 Geekbench ML on macOS 14ĪI and ML-related workflows aren’t just confined to mobile, and hardware architecture on desktop and laptop devices is changing to accommodate this shift in computing. This new preview is available on iOS at the Apple App Store, on Android through the Google Play Store, and newly available for macOS, Windows, and Linux through our downloads page.

As companies continue to deliver newer, faster, and better AI systems and features, our updated frameworks and models make it possible to compare ML performance across devices and platforms with Geekbench’s well-known usability.

The newest preview of Geekbench for ML workloads is now here, delivering several improvements in our testing methodology for even more accurate measurement of real-world performance, as well as support for three entirely new platforms: Geekbench ML is now available on PC, Mac, and Linux.