Geekbench 6, the latest version of the best cross-platform benchmark, has arrived and is loaded with new and improved workloads to measure the performance of your CPUs and GPUs. Geekbench 6 is available for download today for Android, iOS, Windows, macOS, and Linux.
A lot has changed in the tech world in the past three years. Smartphone cameras take bigger and better pictures. Artificial intelligence, especially machine learning, has become ubiquitous in general and mobile applications. The number of cores in computers and mobile devices continues to rise. And how we interact with our computers and mobile devices has changed dramatically – who would have guessed that video conferencing would suddenly surge in 2020?
To keep up with these advancements, we've released Geekbench 6. This latest version of Geekbench has been designed with the modern user in mind, reflecting how we actually use our devices in 2023.
So, what's new in Geekbench 6? Let's take a look!
New and Updated Real-World Tests
Geekbench tests have always been grounded in real-world use cases and use modern. With Geekbench 6, we've taken this to the next level by updating existing workloads and designing several new workloads, including workloads that:
- Blur backgrounds in video conferencing streams
- Filter and adjust images for social media sites
- Automatically remove unwanted objects from photos
- Detect and tag objects in photos using machine learning models
- Analyse, process, and convert text using scripting languages
Modern Data Sets
We also updated the datasets that the workloads process so they better align with the file types and sizes that are common today. This includes:
- Higher-resolution photos in image tests
- Larger maps in navigation tests
- Larger, more complex documents in the PDF and HTML5 Browser tests
- More (and larger) files in the developer tests
True-to-Life Scaling
The multi-core benchmark tests in Geekbench 6 have also undergone a significant overhaul. Rather than assigning separate tasks to each core, the tests now measure how cores cooperate to complete a shared task. This approach improves the relevance of the multi-core tests and is better suited to measuring heterogeneous core performance. This approach follows the growing trend of incorporating "performance" and "efficient" cores in desktops and laptops (not just smartphones and tablets). |
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