A very precise measurement of what a device is capable of doing
Different hardware will have different performance in terms of artificial intelligence. The power of the CPU, GPU, and neural engines, if any, as well as the amount of available power and various other variables directly affect the ability of a device to efficiently run AI models. How to compare devices with so many variables? With the new Primate Labs app: Geekbench AI.
An accurate assessment of the capabilities of each device
The app is capable of analyzing performance under a considerable variety of workloads. For example, we can evaluate performance at different levels of precision: single precision, medium precision, and quantized data. This is an important differentiation because different AI-related tasks require different levels of precision, and not all devices handle these levels in the same way.
After running the test, the tool provides us with a score in three parts that reflects this variety, giving us a more complete view of hardware performance. In addition to performance scores, Geekbench AI also includes a measure of accuracy in each test.
Geekbench, a software already well known for its performance benchmarks, has officially launched Geekbench AI, a suite specifically designed to evaluate the ability of devices in machine learning tasks, deep learning and other AI-focused workloads.
A synthetic test, like the ones we have in front of us, does not always accurately reflect what the device has to face in its day-to-day. And yet, the ability of the Geekbench tools developed by Primate Labs to come as close as possible to these use cases has made their apps and scores a benchmark. A benchmark that we can now use to compare the power of different devices in the field of AI.
Regarding the measurement process, Geekbench AI takes advantage of several new frameworks for a more accurate simulation of workloads. Primate Labs has also made sure to include data sets that accurately reflect typical workloads and inputs in real-world usage.
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