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More than two million XPRT benchmark runs and downloads!

As we near the end of 2024, we’re excited to share that the XPRTs have passed another notable milestone—over 2,000,000 combined runs and downloads! The rate of growth in the total number of XPRT runs and downloads is exciting. It took about seven and a half years for the XPRTs to pass one million total runs and downloads—but it’s taken less than half that, three and a half years, to add another million. Figure 1 shows the climb to the two-million-run mark.

Figure 1: The cumulative number of total yearly XPRT runs and downloads over time.

As you would expect, most of the runs contributing to that total come from WebXPRT tests. If you’ve run WebXPRT in any of the 983 cities and 84 countries from which we’ve received completed test data—including newcomers El Salvador, Malaysia, Morocco, and Saudi Arabia—we’re grateful for your help in reaching this milestone! As Figure 2 illustrates, WebXPRT use has grown steadily since the debut of WebXPRT 2013. On average, we now record more than twice as many WebXPRT runs each month than we recorded in WebXPRT’s entire first year. With over 340,000 runs so far in 2024—an increase of more than 16 percent over last year’s total—that growth is showing no signs of slowing down.

Figure 2: The cumulative number of total yearly WebXPRT runs over time.

This milestone isn’t just about numbers. Establishing and maintaining a presence in the industry and experiencing year-over-year growth requires more than technical know-how and marketing efforts. It requires the ongoing trust and support of the benchmarking community—including OEM labs, the tech press, and independent computer enthusiasts—and those who simply want to know how good their devices are at web browsing.

Once again, we’re thankful for the support of everyone who’s used the XPRTs over the years, and we look forward to another million!

If you have any questions or comments about any of the XPRTs, we’d love to hear from you!

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.

Speaking of potential future WebXPRT workloads

In recent blog posts, we’ve discussed several types of potential future WebXPRT workloads—from an auxiliary AI-focused workload to a WebXPRT battery life test—and many of the factors that we would need to consider when developing those workloads. In today’s post, we’re discussing other types of workloads that we may consider for future WebXPRT versions. We’re also inviting you to send us your WebXPRT workload ideas!

Currently, the most promising web technology for future WebXPRT workloads is WebAssembly (Wasm). Wasm is a binary instruction format that works across all modern browsers, provides a sandboxed environment that operates at native speeds, and takes advantage of common hardware specs across platforms. Wasm’s capabilities offer web developers significant flexibility in running complex client applications within the browser.

We first made use of Wasm in WebXPRT 4’s Organize Album and Encrypt Notes workloads, but Wasm has the potential to support many more types of test scenarios. Here are just a few of the use-case categories that Wasm supports:

  • Gaming
  • Image and video editing
  • Video augmentation
  • CAD applications
  • Interactive learning portals
  • Language translation

Those categories and the possibilities they open for additional workloads are exciting! When thinking through possible new workload scenarios, it’s important to remember that workload proposals need to fit within a set of basic guidelines that uphold WebXPRT’s strengths as a benchmark. You can read about those guidelines in more detail in this blog post, but in short, new workloads ideally should

  • be relevant to real-life scenarios
  • have cross-platform support
  • clearly differentiate in their performance between different types of devices
  • produce consistent and easily replicated results

After testing with WebXPRT or reviewing the list of use cases that Wasm supports, have you considered a new workload or test scenario that you would like to see? If so, please let us know! Your ideas could end up playing a role in shaping the next version of WebXPRT!

Justin

Thinking through a potential WebXPRT 4 battery life test

In recent blog posts, we’ve discussed some of the technical considerations we’re working through on our path toward a future AI-focused WebXPRT 4 auxiliary workload. While we’re especially excited about adding to WebXPRT 4’s AI performance evaluation capabilities, AI is not the only area of potential WebXPRT 4 expansion that we’ve thought about. We’re always open to hearing suggestions for ways we can improve WebXPRT 4, including any workload proposals you may have. Several users have asked about the possibility of a WebXPRT 4 battery life test, so today we’ll discuss what one might look like and some of the challenges we’d have to overcome to make it a reality.

Battery life tests fall into two primary categories: simple rundown tests and performance-weighted tests. Simple rundown tests measure battery life during extreme idle periods and loops of movie playbacks, etc., but do not reflect the wide-ranging mix of activities that characterize a typical day for most users. While they can be useful for performing very specific apples-to-apples comparisons, these tests don’t always give consumers an accurate estimate of the battery life they would experience in daily use.

In contrast, performance-weighted battery life tests, such as the one in CrXPRT 2, attempt to reflect real-world usage. The CrXPRT battery life test simulates common daily usage patterns for Chromebooks by including all the productivity workloads from the performance test, plus video playback, audio playback, and gaming scenarios. It also includes periods of wait/idle time. We believe this mixture of diverse activity and idle time better represents typical real-life behavior patterns. This makes the resulting estimated battery life much more helpful for consumers who are trying to match a device’s capabilities with their real-world needs.

From a technical standpoint, WebXPRT’s cross-platform nature presents us with several challenges that we did not face while developing the CrXPRT battery life test for ChromeOS. While the WebXPRT performance tests run in almost any browser, cross-browser differences and limitations in battery life reporting may restrict any future battery life test to a single browser or browser family. For instance, with the W3C Battery Status API, we can currently query battery status data from non-mobile Chromium-based browsers (e.g., Chrome, Edge, Opera, etc.), but not from Firefox or Safari. If a WebXPRT 4 battery life test supported only a single browser family, such as Chromium-based browsers, would you still be interested in using it? Please let us know.

A browser-based battery life workflow also presents other challenges that we do not face in native client applications, such as CrXPRT:

  • A browser-based battery life test may require the user to check the starting and ending battery capacities, with no way for the app to independently verify data accuracy.
  • The battery life test could require more babysitting in the event of network issues. We can catch network failures and try to handle them by reporting periods of network disconnection, but those interruptions could influence the battery life duration.
  • The factors above could make it difficult to achieve repeatability. One way to address that problem would be to run the test in a standardized lab environment with a steady internet connection, but a long list of standardized environmental requirements would make the battery life test less attractive and less accessible to many testers.

We’re not sharing these thoughts to make a WebXPRT 4 battery life test seem like an impossibility. Rather, we want to offer our perspective on what the test might look like and describe some of the challenges and considerations in play. If you have thoughts about battery life testing, or experience with battery life APIs in one or more of the major browsers, we’d love to hear from you!

Justin

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

In our last blog post, we discussed one of the major decision points we’re facing as we work on what we hope will be the first new AI-focused WebXPRT 4 auxiliary workload: choosing a Web AI framework. In today’s blog, we’re discussing another significant decision that we need to make for the future workload’s development path: choosing a web API.

Many of you are familiar with the concept of an application programming interface (API). Simply put, APIs implement sets of software rules, tools, and/or protocols that serve as intermediaries that make it possible for different computer programs or components to communicate with each other. APIs simplify many development tasks for programmers and provide standardized ways for applications to share data, functions, and system resources.

Web APIs fulfill the intermediary role of an API—through HTTP-based communication—for web servers (on the server side) or web browsers (on the client side). Client-side web APIs make it possible for browser-based applications to expand browser functionality. They execute the kinds of JavaScript, HTML5, and WebAssembly (Wasm) workloads—among other examples—that support the wide variety of browser extensions many of us use every day. WebXPRT uses those types of browser-based workloads to evaluate system performance. To lay a solid foundation for the first future browser-based AI workload, we need to choose a web API that will be compatible with WebXPRT and the Web AI framework and AI inference workload(s) we ultimately choose.

Currently, there are three main web API paths for running AI inference in a web browser: Web Neural Network (WebNN), Wasm, and WebGPU. These three web technologies are in various stages of development and standardization. Each has different levels of support within the major browsers. Here are basic overviews of each of the three options, as well as a few of our thoughts on the benefits and limitations that each may bring to the table for a future WebXPRT AI workload:

  • WebNN is a JavaScript API that enables developers to directly execute machine learning (ML) tasks on neural networks within web-based applications. WebNN makes it easier to integrate ML models into web apps, and it allows web apps to leverage the power of neural processing units (NPUs). WebNN has a lot going for it. It’s hardware-agnostic and works with various ML frameworks. It’s likely to be a major player in future browser-based inference applications. However, as a web standard, WebNN is still in the development stage and is only available in developer previews for Chromium-based browsers. Full default WebNN support could take a year or more.
  • Wasm is a binary instruction format that works across all modern browsers. Wasm provides a sandboxed environment that operates at near-native speeds and takes advantage of common hardware specs across platforms. Wasm’s capabilities offer web developers a great deal of flexibility for running complex client applications in the browser. Simply put, Wasm can help developers adapt their existing code for additional platforms and browser-based applications without requiring extensive code rewrites. Wasm’s flexibility and cross-platform compatibility is one of the reasons that we’ve already made use of Wasm in two existing WebXPRT 4 workloads that feature AI tasks: Organize Album using AI, and Encrypt Notes and OCR Scan. Wasm can also work together with other web APIs, such as WebGPU.
  • WebGPU enables web-based applications to directly access the graphics rendering and computational capabilities of a system’s GPU. The parallel computational abilities of GPUs make them especially well-suited to efficiently handle some of the demands of AI inference workloads, including image-based GenAI workloads or large language models. Google Chrome and Microsoft Edge currently support WebGPU, and it’s available in Safari through a tech preview.

Right now, we don’t think that WebNN will be fully out of the development phase in time to serve as our go-to web API for a new WebXPRT AI workload. Wasm and/or WebGPU appear to our best options for now. When WebNN is fully baked and available in mainstream browsers, it’s possible that we could port any existing Wasm- or WebGPU-based WebXPRT AI workloads to WebNN, which may open the possibility of cross-platform browser-based NPU performance comparisons.

All that said and as we mentioned in our previous post about Web AI frameworks, we have not made any final decisions about a web API or any aspect of the future workload. We’re still in the early stages of this project. We want your input.

If this discussion has sparked web AI ideas that you think would benefit the process, or if you have feedback you’d like to share, please feel free to contact us!

Justin

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