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WebXPRT 5: The workload lineup

on December 8, 2025

The WebXPRT 5 development process heading into the final stretch, so we’d like to share more information about the workloads you’re likely to see in the WebXPRT 5 Preview release—and when that release may be available. We’re still actively testing candidate builds, studying results from multiple system tests, and so on, so some details could change. That said, we’re now close enough to provide a clearer picture of the workload lineup.

Core workloads

WebXPRT 5 will likely include the following seven workloads:

Video Background Blur with AI. Blurs the background of a video call using an AI-powered Segmentation model.
Photo Effects. Applies a filter to six photos using the Canvas API.
Detect Faces with AI. Detects faces and organizes photos in an album using computer vision (OpenCV.js with Caffe Model).
Image Classification with AI. Labels images in an album using machine learning (OpenCV.js and ML Classify with the SqueezeNet model).
Document Scan with AI. Scans a document image and converts it to text using ML-based OCR (Wasm with LSTM).
School Science Project. Processes a DNA sequencing task using Regex and String manipulation.
Homework Spellcheck. Spellchecks a document using Typo.js and Web Workers.

The sub-scores for each of these tests will contribute to WebXPRT 5’s main overall score. (We’ll discuss scoring in future blogs.)

Experimental workloads

We’re currently planning to include an experimental workload section, something we’ve long discussed, in WebXPRT 5. Workloads in this section will use cutting-edge browser technologies that may not be compatible with the same broad range of platforms and devices as the technologies in WebXPRT 5’s core workloads. For that reason, we will not include the scores from the experimental section—in the Preview build and future releases—in WebXPRT 5’s main overall score.

In addition, WebXPRT 5’s experimental workloads will be completely optional.

Moving forward, WebXPRT’s experimental workload section will provide users with a straightforward way to learn how well certain browsers or systems handle new browser-based technologies (e.g., new web apps or AI capabilities). We’ll benefit from the ability to offer workloads for large-scale testing and user feedback before committing to including them as core WebXPRT workloads. Because future experimental workloads will run independently of the main test, we can add them without affecting the main WebXPRT score or requiring users to repeat testing to obtain comparable scores. We think it will be a win-win scenario in many respects.

We’re still evaluating whether we can finish the first experimental workload in time to include it in the WebXPRT 5 Preview release, but we will definitely have at least the section and the framework for adding such a workload. When we are confident that an experimental workload is ready to go, we’ll share more information here in the blog and be all set up to incorporate it.

Timeline

If all goes well, we hope to publish the WebXPRT 5 Preview very soon, followed by a general release in early 2026. If that timeline changes significantly, we’ll provide an update here in the blog as soon as possible.

What about an “AI score”?

We’re still discussing the concept of a stand-alone WebXPRT 5 “AI score,” and we go back and forth on it. That score would combine WebXPRT’s AI-related subscores into a single score for use in AI capability comparisons. Because we’re just now beefing up WebXPRT’s AI capabilities, we’ve definitely decided not to include an AI score right now. We would love your feedback on the concept as we plan WebXPRT’s future. If that’s something that you would be interested in, please let us know!

If you have any questions about the WebXPRT 5 details we’ve shared above, please feel free to ask!

Justin

Posted in AI, benchmark, BenchmarkXPRT, BenchmarkXPRT development community, browser performance, Browser-based benchmarks, Caffe, Collaborative benchmark development, Cross-platform benchmarks, Future of performance evaluation, image classification, image processing, JavaScript, LAMP, on-device AI, Performance benchmarking, Performance of computing devices, SqueezeNet, Wasm, Web AI, web API, Web-based testing, WebXPRT, WebXPRT 4, WebXPRT 5 | Also tagged AI, artificial intelligence, benchmark, BenchmarkXPRT, BenchmarkXPRT Development Community, browser benchmark, browser performance, Caffe Model, Canvas API, LLM, LSTM, machine learning, ML, OCR, OpenCV, SLM, Small Language Model, WASM, Web Workers, WebXPRT, WebXPRT 4, WebXPRT 5

WebXPRT 5: Starting to assemble the pieces

By Justin Greene

on November 6, 2025

In our last blog post, we shared the exciting news that we’re currently working on WebXPRT 5. In that post, we described some of the ways that WebXPRT may evolve with the release of WebXPRT 5. In today’s post, we’ll revisit some of the points of emphasis from the last post and focus on potential workload changes in a bit more detail.

With any benchmark development project, there are always technical challenges you need to iron out. That is especially true with a cross-platform, browser-based benchmark like WebXPRT. Because we’re in the middle of exploring the technical feasibility of a few of the options we’ll mention, we’re not yet ready to say for certain that all these features will be available in the initial WebXPRT 5 release. We can, however, now paint a clearer picture of the overall direction we’re headed.

In the section below, you’ll find updated info on where we stand with respect to some of the key development focal points we discussed in our last post. If there’s an item from that post or previous posts that we didn’t mention below—such as updating the test harness—it doesn’t mean that we’re dropping that goal. We’re just focusing on workloads today.

One of our key goals with WebXPRT 5 is providing more AI-related workloads. In past blog posts, we’ve discussed the growing importance of local, browser-side AI. With WebXPRT 5, we’re investigating two ways that we can expand WebXPRT’s AI portfolio: 1) updating existing WebXPRT 4 AI-oriented workloads, and 2) adding all-new AI workloads.

Here are some possible ways those AI-related changes may play out in both categories:

Updating existing WebXPRT 4 AI-oriented workloads

Splitting the existing Organize Album using AI workload’s timed tasks—face detection and image classification—into two independent workloads.
Updating the face detection and image classification tasks with the latest versions of the OpenCV.js computer vision and machine learning libraries.
Updating the Caffe deep learning framework for the face detection task.
Updating the ONNX-based SqueezeNet machine learning model for the image classification tasks.
Updating the version of the Tesseract.js OCR engine that WebXPRT uses in the Encrypt Notes and OCR Scan workload.

Potentially adding all-new AI workloads (either core or experimental workloads)

We’re exploring the idea of including a workload that uses an AI-powered segmentation model to blur the background of a video call.
We’re exploring the feasibility of including a local LLM chat workload.
We would eventually like to include a WebGPU-based web AI framework for a computer vision workload.

In addition to the goal of adding more AI, we previously discussed the possibility of adding non-AI WebGPU workloads. As a web API, WebGPU enables web-based applications—such as image-based GenAI and inference workloads—to directly access the graphics rendering and computational capabilities of a system’s GPU. In the future, WebXPRT 5 could use that technology to execute complex 3D rendering workloads.

We hope today’s post gives you a better sense of where WebXPRT 5 may be headed. We want to reemphasize that while we are actively investigating the possible changes mentioned above, nothing is set in stone. As the pieces start to fall into place, we’ll provide more information here in the blog.

If you have any questions or comments about WebXPRT 5, please feel free to contact us!