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Recent XPRT mentions in articles, reviews, and more!

Here at the XPRTs, our primary goal is to provide free, easy-to-use benchmark tools that can help everyone—from OEM labs to tech press journalists to individual consumers—understand how well devices will perform while completing everyday computing tasks. We track progress toward that goal in several ways, but one of the most important is how much people use and discuss the XPRTs. When the name of one of our apps appears in an ad, article, or tech review, we call it a “mention.” Tracking mentions helps us gauge our reach.

We occasionally like to share a sample of recent XPRT mentions here in the blog. If you just started following the XPRTs, it may be surprising to see our program’s global reach. If you’re a longtime reader and you’re used to seeing WebXPRT or CrXPRT in major tech press articles, it may be surprising to learn more about overseas tech press publications or see how some government agencies use the XPRTs to make decisions. In any case, we hope you’ll enjoy exploring the links below!

Recent mentions include:

If you’d like to receive monthly updates on XPRT-related news and activity, we encourage you to sign up for the BenchmarkXPRT Development Community newsletter. It’s completely free, and all you need to do to join the newsletter mailing list is let us know! We won’t publish, share, or sell any of the contact information you provide, and we’ll only send you the monthly newsletter and occasional benchmark-related announcements, such as important news about patches or releases.

If you have any questions about the XPRTs, suggestions, or requests for future blog topics, please feel free to contact us.

Justin

Archiving AIXPRT and CloudXPRT

Some of our readers have been following the XPRTs since the early days, and they may remember using legacy versions of benchmarks such as HDXPRT 2014 or WebXPRT 2013. For many years, whenever we released a new version of a benchmark, we would maintain a link to the previous version on the benchmark’s main page. However, as interest in the older versions understandably waned and we stopped formally supporting them, many of those legacy XPRTs stopped working on the latest versions of the operating systems or browsers that we designed them to test. While we wanted to continue to provide a way for users to access those legacy XPRTs, we also wanted to avoid potential confusion for new users who might see links to old versions on our site. We decided that the best solution was to archive older tests in a separate section of the site—the XPRT archive.

Recently, as we discussed XPRT plans for 2025, it became clear that we needed to add AIXPRT and CloudXPRT to the archive. Both benchmarks represent landmark efforts toward our ongoing goal of providing cutting-edge performance assessment tools, but even though a few tech press publications and OEM labs experimented with them, neither benchmark gained enough widespread adoption to justify their continued support. As a result, we decided to focus our resources elsewhere and halt development on both benchmarks. Since then, ongoing updates to their respective software components and target platforms have rendered them largely unusable. By archiving both benchmarks, we hope to avoid any future confusion for visitors who may otherwise try to use them.

Over the coming weeks, we’ll be moving the AIXPRT and CloudXPRT installation packages to the XPRT archive page. We’re grateful to everyone who has used AIXPRT and CloudXPRT in the past, and we apologize for any inconvenience this change may cause.

If you have any questions or concerns about access to either of these benchmarks—or about anything else related to the XPRTs, please let us know

Justin

Check out the new XPRTs around the world infographic!

As we look forward to continued growth for the XPRTs in 2025, it’s also a fitting time to take stock of just how much their reach has already grown around the globe. In the marketing world, reach is often defined as the size of the audience that sees and/or engages with your content. We track XPRT reach with several metrics—including completed test runs, benchmark downloads, and mentions of the XPRTs in advertisements, articles, and tech reviews. Gathering this information gives us insight into how many people are using the XPRTs, and it provides a sense of the impact the XPRTs are having around the world. It also helps us understand the needs of those who use them.

From time to time, we publish an updated version of an “XPRTs around the world” infographic, which features highlights from the reach metrics we track. This week, we published a new version of the infographic that includes the following highlights:

  • Over 4,100 unique sites have collectively mentioned the XPRTs more than 20,500 times.
  • Those mentions include more than 12,900 tech articles and reviews.
  • XPRT tech press mentions and test runs have originated in over 983 cities located in 84 countries on six continents. New cities of note include San Salvador, El Salvador; Salamanca, Mexico; Fes, Morocco; Wanaka, New Zealand; and Luzern, Switzerland.

In addition to the reach metrics we mention above, the XPRTs have now delivered more than 2,020,000 real-world results! We’re grateful for everyone who’s used the XPRTs and has spread the word to others. Your active involvement makes it possible for us to achieve our overall goals: to provide benchmark tools that are reliable, relevant, free, and simple to use.

Justin

Using WebXPRT 4’s language options

Sohu, a major Chinese site, recently published a tech review discussing their first impressions from Intel Core Ultra 5 245K and Intel Core Ultra 9 285K white box testing. In the article, they included screenshots of the WebXPRT 4 test results they produced during their evaluation. The screenshots showed that the testers had enabled WebXPRT 4’s Simplified Chinese UI. They’re not the first to use this option, and it’s one we are glad worked for them.

Though WebXPRT’s language settings menu has proven to be a popular feature for many users around the world, some folks may not even know the option is there. In today’s blog, we’ll go over the basics of this simple but helpful testing option.

On WebXPRT’s Start screen, you can choose from three language options in the WebXPRT 4 UI: Simplified Chinese, German, and English. We included Simplified Chinese and German because of the large number of tests we see from China and Central Europe. We wanted to make testing a little easier for users who prefer those languages and we’re glad to see people using the options.

Changing languages in the WebXPRT UI is quick and easy. Locate the “Change Language?” prompt under the WebXPRT 4 logo at the top of the Start screen, and click or tap the arrow beside it. After the drop-down menu appears, select the language you want. The language of the start screen will then change to the language you selected, and the in-test workload headers and end-of-test results screen will also appear in the language you selected.

Figures 1–3 below my sig show the “Change Language?” drop-down menu and how the Start screen appears when you select Simplified Chinese or German. It’s important to note that if you have a translation extension installed in your browser, it may override the WebXPRT UI by reverting the language back to your browser’s default. You can avoid this conflict by temporarily disabling the browser’s translation extension for the duration of WebXPRT testing.

We hope WebXPRT 4’s language options will help facilitate the testing process for many users around the world. If you’re a frequent WebXPRT user and would like to see us add support for another language, please contact us. And, of course, if you have any questions about WebXPRT 4 testing, please let us know!

Justin

Figure 1: A screenshot of the WebXPRT 4 Start screen showing the language options drop-down menu.
Figure 2: A screenshot of the WebXPRT 4 Start screen with a Simplified Chinese UI.
Figure 3: A screenshot of the WebXPRT 4 Start screen with a German UI.

Gain a deeper understanding of WebXPRT 4 with our results calculation white paper

More people around the world are using WebXPRT 4 now than ever before. It’s exciting to see that growth, which also means that many people are visiting our site and learning about the XPRTs for the first time. Because new visitors may not know how the XPRT family of benchmarks differs from other benchmarking efforts, we occasionally like to revisit the core values of our open development community here in the blog—and show how those values translate into more free resources for you.

One of our primary values is transparency in all our benchmark development and testing processes. We share information about our progress with XPRT users throughout the development process, and we invite people to contribute ideas and feedback along the way. We also publish both the source code of our benchmarks and detailed information about how they work, unlike benchmarks that use a “black box” model.

For WebXPRT 4 users who are interested in knowing more about the nuts and bolts of the benchmark, we offer several information-packed resources, including our focus for today, the WebXPRT 4 results calculation and confidence interval white paper. The white paper explains the WebXPRT 4 confidence interval, how it differs from typical benchmark variability, and the formulas the benchmark uses to calculate the individual workload scenario scores and overall score on the end-of-test results screen. The paper also provides an overview of the statistical methodology that WebXPRT uses to translate raw timings into scores.

In addition to the white paper’s discussion of the results calculation process, we’ve also provided a results calculation spreadsheet that shows the raw data from a sample test run and reproduces the calculations WebXPRT uses to generate both the workload scores and an overall score.

In potential future versions of WebXPRT, it’s likely that we’ll continue to use the same—or very similar—statistical methodologies and results calculation formulas that we’ve documented in the results calculation white paper and spreadsheet. That said, if you have suggestions for how we could improve those methods or formulas—either in part or in whole—please don’t hesitate to contact us. We’re interested in hearing your ideas!

The white paper is available on WebXPRT.com and on our XPRT white papers page. If you have any questions about the paper or spreadsheet, WebXPRT, or the XPRTs in general, please let us know.

Justin

Web AI frameworks: Possible paths for the AI-focused WebXPRT 4 auxiliary workload

A few months ago, we announced that we’re moving forward with the development of a new auxiliary WebXPRT 4 workload focused on local, browser-side AI technology. Local AI has many potential benefits, and it now seems safe to say that it will be a common fixture of everyday life for many people in the future. As the growth of browser-based inference technology picks up steam, our goal is to equip WebXPRT 4 users with the ability to quickly and reliably evaluate how well devices can handle substantial local inference tasks in the browser.

To reach our goal, we’ll need to make many well-researched and carefully considered decisions along the development path. Throughout the decision-making process, we’ll be balancing our commitment to core XPRT values, such as ease of use and widespread compatibility, with the practical realities of working with rapidly changing emergent technologies. In today’s blog, we’re discussing one of the first decision points that we face—choosing a Web AI framework.

AI frameworks are suites of tools and libraries that serve as building blocks for developers to create new AI-based models and apps or integrate existing AI functions in custom ways. AI frameworks can be commercial, such as OpenAI, or open source, such as Hugging Face, PyTorch, and TensorFlow. Because the XPRTs are available at no cost for users and we publish our source code, open-source frameworks are the right choice for WebXPRT.

Because the new workload will focus on locally powered, browser-based inference tasks, we also need to choose an AI framework that has browser integration capabilities and does not rely on server-side computing. These types of frameworks—called Web AI—use JavaScript (JS) APIs and other web technologies, such as WebAssembly and WebGPU, to run machine learning (ML) tasks on a device’s CPU, GPU, or NPU.

Several emerging Web AI frameworks may provide the compatibility and functionality we need for the future WebXPRT workload. Here are a few that we’re currently researching:

  • ONNX Runtime Web: Microsoft and other partners developed the Open Neural Network Exchange (ONNX) as an open standard for ML models. With available tools, users can convert models from several AI frameworks to ONNX, which can then be used by ONNX Runtime Web. ONNX Runtime Web allows developers to leverage the broad compatibility of ONNX-formatted ML models—including pre-trained vision, language, and GenAI models—in their web applications.
  • Transformers.js: Transformers.js, which uses ONNX Runtime Web, is a JS library that allows users to run AI models from the browser and offline. Transformers.js supports language, computer vision, and audio ML models, among others.
  • MediaPipe: Google developed MediaPipe as a way for developers to adapt TensorFlow-based models for use across many platforms in real-time on-device inference applications such as face detection and gesture recognition. MediaPipe is particularly useful for inference work in images, videos, and live streaming.
  • TensorFlow.js: TensorFlow has been around for a long time, and the TensorFlow ecosystem provides users with a broad variety of models and datasets. TensorFlow is an end-to-end ML solution—training to inference—but with available pre-trained models, developers can focus on inference. TensorFlow.js is an open-source JS library that helps developers integrate TensorFlow with web apps.

We have not made final decisions about a Web AI framework or any aspect of the future workload. We’re still in the research, discussion, and experimentation stages of development, but we want to be transparent with our readers about where we are in the process. In future blog posts, we’ll discuss some of the other major decision points in play.

Most of all, we invite you to join us in these discussions, make recommendations, and give us any other feedback or suggestions you may have, so please feel free to share your thoughts!

Justin

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