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[#]: subject: "Geekbench ML Benchmark App Adds Linux Desktop Support"
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[#]: via: "https://news.itsfoss.com/geekbench-ml-benchmark-app/"
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[#]: author: "Sourav Rudra https://news.itsfoss.com/author/sourav/"
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[#]: collector: "lujun9972/lctt-scripts-1700446145"
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[#]: translator: "geekpi"
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[#]: reviewer: " "
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[#]: publisher: " "
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[#]: url: " "
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Geekbench ML Benchmark App Adds Linux Desktop Support
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======
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Test your machine for ML workload capabilities!
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In a year when we have seen a [new AI alliance][1] being formed, and some questioning the [open-source definition for AI models][2], we are still seeing plenty of new developments.
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One such development has been in the field of AI benchmarking, the popular Geekbench ML has done something really cool with its latest release.
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**What's Happening:** With a [recent announcement][3], [Primate Labs][4] have announced the release of **Geekbench ML 0.6** , with **an early Christmas gift in the form of support for Linux.**
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Released as **a preview version** , this release of Geekbench ML is now available for **Linux** , **Windows** , and **macOS**.
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**What to Expect:** Well, for starters, you can **expect the benchmarking experience to be the same** across all the platforms, as they all use the same models and data sets.
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Which, by the way, have been improved thanks to the **implementation of new frameworks** that bring in upgrades to Geekbeench's internal version of [TensorFlow Lite][5].
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They have also added **three new types of workloads** with the Geekbench ML 0.6 release:
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* **Depth Estimation** , a workload that will help simulate common camera software effects.
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* **Style Transfer** , a workload that will simulate how generative AI functions for common use cases such as copying the style of a photo to create something different.
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* **Image Super-Resolution** , a workload that will simulate AI-powered image upscaling.
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But, there is one important thing to note. **For Linux, there is no graphical user interface (GUI) with Geekbench ML 0.6** , users will have to make do with a command-line-tool; more on that later.
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So, even though we are still a bit away from the **Geekbench ML 1.0 release, which is planned to be made available sometime in 2024** , this is a decent one that has some niggles here and there. But, I am glad to see that they are providing a port for Linux.
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Seeing as we are on the topic; d **o you want to run Geekbench ML on your Linux system?**
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## **Here's How to Run a Geekbench ML Benchmark**
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Well, firstly, you will have to download the _tar.gz_ archive from the Geekbench site (linked below).
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Thereafter, extract it, open a terminal window in the same directory, and run the following command:
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```
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./banff
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```
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📋
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Ensure that you have a working internet connection before running the benchmark.
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![][6]
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It should then start running the benchmark, you will be shown which model and data sets are being run in real-time.
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![][7]
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After the benchmarking is done, a confirmation with a prompt will be shown, that guides you to view the benchmarking results online.
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![][8]
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You can find my benchmarking results on [Geekbench Browser][9], I admit it is not much, but, it is my system's humble score 😄
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For running Geekbench ML on Linux, the developers recommend the following **system requirements** :
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* **CPU:** AMD or Intel
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* **RAM:** Minimum 2 GB
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* **OS:** Ubuntu 18.04 LTS (64-bit) or later
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You can grab the _tar.gz_ from the [official website][10], just extract it and get started.
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[Geekbench ML][10]
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_💬 I really hope they add a GUI with the future releases of Geekbench ML for Linux. What do you think?_
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* * *
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--------------------------------------------------------------------------------
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via: https://news.itsfoss.com/geekbench-ml-benchmark-app/
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作者：[Sourav Rudra][a]
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选题：[lujun9972][b]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://news.itsfoss.com/author/sourav/
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[b]: https://github.com/lujun9972
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[1]: https://news.itsfoss.com/ai-alliance/
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[2]: https://news.itsfoss.com/open-source-definition-ai/
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[3]: https://www.geekbench.com/blog/2023/12/geekbench-ml-06/
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[4]: https://www.primatelabs.com/
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[5]: https://www.tensorflow.org/lite/guide
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[6]: https://news.itsfoss.com/content/images/2023/12/Geekbench_ML_0.6.png
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[7]: https://news.itsfoss.com/content/images/2023/12/Geekbench_ML_0.6_Output-1.png
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[8]: https://news.itsfoss.com/content/images/2023/12/Geekbench_ML_0.6_Output_2.png
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[9]: https://browser.geekbench.com/ml/v0/inference/328997
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[10]: https://www.geekbench.com/ml/download/
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