The Origin Trial will start in M-146 and run through M-148. Developers can
sign up for trial keys:

   - Chrome:
   https://developer.chrome.com/origintrials/#/view_trial/2250110963824984065
   - Edge:
   
https://developer.microsoft.com/en-us/microsoft-edge/origin-trials/trials/19857284-cf52-484b-8b09-8ca50ac9dccb

Reilly Grant | Software Engineer | [email protected] | Google Chrome
<https://www.google.com/chrome>


On Mon, Jan 5, 2026 at 7:29 PM Reilly Grant <[email protected]> wrote:

> Due to release-blocking issues, we are delaying the start of the Origin
> Trial by at least a release. I will update this thread when we have a new
> starting milestone.
> Reilly Grant | Software Engineer | [email protected] | Google Chrome
> <https://www.google.com/chrome>
>
>
> On Fri, Dec 19, 2025 at 1:09 PM Rick Byers <[email protected]> wrote:
>
>> Glad to see this in OT, hope to see some cool things in the wild soon!
>> LGTM to experiment 145-147 inclusive.
>>
>> On Fri, Dec 19, 2025 at 2:52 PM Reilly Grant <[email protected]>
>> wrote:
>>
>>> On Friday, December 19, 2025 at 11:50:19 AM UTC-8 Chromestatus wrote:
>>>
>>> *Contact emails*
>>> [email protected], [email protected], [email protected],
>>> [email protected]
>>>
>>> *Explainer*
>>> https://github.com/webmachinelearning/webnn/blob/main/explainer.md
>>>
>>> *Specification*
>>> https://webmachinelearning.github.io/webnn
>>>
>>> *Design docs*
>>>
>>> https://docs.google.com/document/d/1kIc5NO1PU1DbGHKOsnan-
>>> tEhV01L6_K3OLA5g0o4Ts4/edit?resourcekey=0-ltUDiDZqxKgARhtNqsGJeg
>>>
>>> *Summary*
>>> WebNN seeks to enable web applications and frameworks to take advantage
>>> of native operating system services for machine learning and the underlying
>>> hardware capabilities available on a user's computer to implement
>>> consistent, efficient, and reliable ML experiences on the web.
>>>
>>> *Blink component*
>>> Blink>WebML
>>> <https://issues.chromium.org/issues?q=customfield1222907:%22Blink%3EWebML%22>
>>>
>>> *Web Feature ID*
>>> webnn <https://webstatus.dev/features/webnn>
>>>
>>> *TAG review*
>>> https://github.com/w3ctag/design-reviews/issues/933
>>>
>>> *TAG review status*
>>> Issues addressed
>>>
>>> *Origin Trial documentation link*
>>> https://webnn.io/en/learn/get-started/quickstart
>>>
>>> *Risks*
>>>
>>>
>>> *Interoperability and Compatibility*
>>> Aside from the risk that other browsers do not implement (which is
>>> trending towards unlikely given that Edge is planning to ship alongside
>>> Chrome and Firefox is planning to implement) the primary interoperability
>>> risk is that a WebNN implementation needs to abstract over the ML
>>> acceleration capabilities of the underlying platform and hardware. The
>>> specification mitigates this risk by defining a set of ML operations which
>>> must be supported and provides a feature detection mechanism for
>>> discovering additional operations that may be optionally supported. This
>>> allows developers to write broadly interoperable code by using only the
>>> required operations or design their applications to adapt to additional
>>> capabilities at runtime.
>>>
>>> *Gecko*: Positive (https://github.com/mozilla/standards-positions/
>>> issues/1215#issuecomment-3520278819)
>>>
>>> *WebKit*: No signal (https://github.com/WebKit/standards-positions/
>>> issues/486) Apple is participating in the WebML WG but has made no
>>> public statements about implementation.
>>>
>>> *Web developers*: Positive Microsoft's ONNX runtime includes an
>>> execution provider for WebNN (https://onnxruntime.ai/docs/
>>> tutorials/web/ep-webnn.html). Google's LiteRT.js framework has
>>> announced that they are working on WebNN support (
>>> https://youtu.be/HAjotVloAvI?t=219).
>>>
>>> *Other signals*: The WebNN implementation in Chromium is a
>>> collaboration between Google, Intel, and Microsoft. Edge will be launching
>>> WebNN at the same time as Chrome.
>>>
>>> *Ergonomics*
>>> For some use cases, particularly real-time ML processing of video,
>>> integration between WebNN and WebGPU is required. Support for this has been
>>> prototyped on some platforms as an `exportToGPU()` method that takes an
>>> `MLTensor` and makes it available as a `GPUBuffer` but this is not yet
>>> available on all platforms.
>>>
>>> *Activation*
>>> Most developers don't write JavaScript or WebGPU shader code to execute
>>> their ML models by hand. Instead frameworks such as LiteRT.js, ONNX Runtime
>>> Web, WebLLM or Transformers.js are used. Support for WebNN in these
>>> frameworks (already starting to appear) will be a large factor in the
>>> adoption of this API.
>>>
>>> *Security*
>>> The primary security risk is exposing the underlying platform frameworks
>>> to potentially malicious content. This is mitigated through sandboxing of
>>> the GPU process and fuzz testing. The risks are similar to WebGPU, though
>>> the expressiveness of WebNN is lower than WGSL.
>>>
>>> *WebView application risks*
>>>
>>> Does this intent deprecate or change behavior of existing APIs, such
>>> that it has potentially high risk for Android WebView-based applications?
>>> This is a new API.
>>>
>>>
>>> *Goals for experimentation*
>>> *No information provided*
>>>
>>>
>>> Due to GoogleChrome/chromium-dashboard#4155
>>> <https://github.com/GoogleChrome/chromium-dashboard/issues/4155> this
>>> wasn't filled in. It should read:
>>>
>>> The goal of this experiment is to understand how well real-world models
>>> abstract to the operations supported by WebNN and how well WebNN can map
>>> these operations to those supported by the hardware of real-world users.
>>>
>>>
>>> *Ongoing technical constraints*
>>> WebNN can currently execute models on CPU across all platforms but
>>> support for GPU and NPU execution is more limited. This will expand as
>>> development continues.
>>>
>>> *Debuggability*
>>> There is currently no special DevTools support for this API beyond
>>> regular JavaScript debugging. A feature we have considered (and prototyped
>>> via an internal extension and the --webnn-coreml-dump-model,
>>> --webnn-ort-dump-model, and --webnn-tflite-dump-model browser flags) is
>>> inspecting graphs constructed by a site and exporting them in the
>>> underlying platform format so that they can be inspected with other tools.
>>>
>>> *Will this feature be supported on all six Blink platforms (Windows,
>>> Mac, Linux, ChromeOS, Android, and Android WebView)?*
>>> Yes
>>>
>>> *Is this feature fully tested by web-platform-tests
>>> <https://chromium.googlesource.com/chromium/src/+/main/docs/testing/web_platform_tests.md>?*
>>> Yes
>>> https://wpt.fyi/results/webnn?label=master&label=
>>> experimental&aligned&q=webnn
>>>
>>> *DevTrial instructions*
>>> https://webnn.io/en/learn/get-started/installation
>>>
>>> *Flag name on about://flags*
>>> web-machine-learning-neural-network
>>>
>>> *Finch feature name*
>>> WebMachineLearningNeuralNetwork
>>>
>>> *Requires code in //chrome?*
>>> True
>>>
>>> *Tracking bug*
>>> https://issues.chromium.org/issues/40206287
>>>
>>> *Estimated milestones*
>>> Origin trial desktop first145 Origin trial desktop last147 DevTrial on
>>> desktop125 Origin trial Android first145 Origin trial Android last147 
>>> DevTrial
>>> on Android125 Origin trial WebView first145 Origin trial WebView last147
>>>
>>> *Link to entry on the Chrome Platform Status*
>>> https://chromestatus.com/feature/5176273954144256?gate=5186064701194240
>>>
>>> *Links to previous Intent discussions*
>>> Intent to Prototype: https://groups.google.com/a/
>>> chromium.org/g/blink-dev/c/PD6TDMDS9mg
>>>
>>>
>>> This intent message was generated by Chrome Platform Status
>>> <https://chromestatus.com>.
>>>
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>>> .
>>>
>>

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