Is GitHub Copilot the best positioned platform for enterprise? They support Claude, GPT, Gemini, and now even open weight models. Larger orgs are paying at API rates anyway so it costs just as much as anywhere else. They have a pretty good agent CLI and SDK, and now a desktop app. They have hosted agents, and you can run their 'Agentic Workflows' in CI.
Has their reputation tanked so much that the alternatives get all the buzz? Or is it that non-enterprise users are priced out by the usage costs, so no free marketing?
It's based on a Gemma 3n model, and yeah it's not the best. But if you have a use case that needs constrained JSON output for example, it's pretty neat.
Maybe it would do better with the new Gemma 4 models, which the Chrome devs have been hinting at moving to. And why the API doesn't let you introspect / pick the model, I'm still not sure.
As OP says, it shines in constrained environments where the model is transforming user-owned data. Definitely less useful for anything more open-ended.
Chromium mostly does not support this, because it doesn't have the binary blob required to run the inference. However, it does still download the model weights and expose the LanguageModel API, because that part is hooked up.
Packagers might eventually disable that but I tested this behaviour in chromium 148 a few hours ago, and it would download the weights but has trouble running them.
Depends on where you get it. By default the flags will be enabled, but some packagers may choose to disable them. I haven't seen a major distro release chromium 148 yet.
Weirdly though, chromium won't be able to actually use the model even though it can download it, because the inference engine is a closed-source blob.
Chromium doesn't support this API because it needs a binary blob to run the inference, although in theory it may still be configured to download the weights:
Author here. After trying out the Prompt API over the last week, I wrote up some details on the chromium internals, how to use the API, and made some toy demos.
It's a 4 GB model that can be used to run on-device inference.
If Chrome has the #optimization-guide-on-device-model and #prompt-api-for-gemini-nano flags enabled, either because it's part of some Origin Trial / Early Stable Release or something, then web pages will have access to the new Prompt API which allows any webpage to initiate the (one-time) download of the ~2.7 GiB CPU or ~4.0 GiB GPU model using LanguageModel.create()
When Chrome 148 releases tomorrow, this will be the default behaviour on desktop.
To download, it should check for 22 GiB free disk space on the volume where your Chrome data dir is, and at least double the model size of free space in your tmp dir.