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Can you provide any sources for that? I'd like to learn more about this open frontier model.

sigmoid10 5mo ago
Sources for what? The pareto frontier of LLMs? How Google is pretty much on the line with most of their LLM products? Or this particular model? For the first two you need to look for size/cost vs. accuracy charts. There are tons of them floating around. For the latter there is not much official info except what you can infer by analyzing the weights.bin file that Chrome downloads. But it does mention Gemini in there, so it seems pretty obvious that it is from their proprietary line of models.
- HumanOstrich 5mo ago
  Sources for your claim that the model being downloaded to Android/Chrome is Gemini instead of Gemma. Other than downloading the bin file myself and analyzing it lol.
  - sigmoid10 5mo ago
    How about Google itself? https://developer.chrome.com/docs/ai/prompt-api https://developer.chrome.com/docs/ai/prompt-api >With the Prompt API, you can send natural language requests to Gemini Nano in the browser.
    - deleted 5mo ago
      [deleted]
    - HumanOstrich 5mo ago
      Thanks. Looks like the current Gemini Nano is actually a separate model with the Gemma 3n architecture that has been distilled from Gemini 2.5 Flash[1]. Also, the next version of Gemini Nano will be based directly on Gemma 4 (so not distilled, not Gemini at all except for the name)[2]. So no, it's not a frontier model. Those don't run on your phone or in your browser. [1]: https://developer.android.com/blog/posts/ml-kit-s-prompt-api-unlock-custom-on-device-gemini-nano-experiences https://developer.android.com/blog/posts/ml-kit-s-prompt-api... [2]: https://android-developers.googleblog.com/2026/04/AI-Core-Developer-Preview.html https://android-developers.googleblog.com/2026/04/AI-Core-De...
      - sigmoid10 4mo ago
        Oh, now I see your problem. You confused the pareto frontier with the pure scale frontier. They are very much not the same. Also, distillation is how most of these smaller models are made from the biggest models. That process largely defines the frontier along most of the curve.
        HumanOstrich 4mo ago
        > This also makes it the only open American frontier-level model right now. I'm not going to keep arguing with you. If you want to keep arguing, go to https://gemini.google.com/ https://gemini.google.com/. Gemini knows what a frontier model is and it knows that Gemini Nano is fundamentally different from the other Gemini models. For one, it uses the Gemma architecture. And the next version of Gemini Nano is built directly on Gemma 4. As for your original claim that I quoted, there are other "open American frontier-level models" by your definition. Like Gemma 4.
        sigmoid10 4mo ago
        I'm surprised how you try to evade the facts and even try to bring in Gemini in a vain attempt to support your argumentation, when a simple google search would have already pointed you at things like this: https://cloud.google.com/blog/topics/developers-practitioners/five-techniques-to-reach-the-efficient-frontier-of-llm-inference https://cloud.google.com/blog/topics/developers-practitioner... or this: https://arena.ai/leaderboard/text/overall/pareto https://arena.ai/leaderboard/text/overall/pareto The lines in these charts is literally what the frontier is on a technical level. None of what I said has any ambiguous terminology. This is common language in the field. Neither is the fact that google cares a lot about this. I don't see why you still feel the need to argue about any of this.
- lxgr 5mo ago
  Just because it's called Gemini doesn't mean that it's somehow automatically as comparable with the frontier of small models as well, does it?
  - sigmoid10 5mo ago
    All Gemini models sit around the frontier, especially if you go to smaller sizes. Google is actually more invested into efficiency than size unlike some of the other big providers.
    - lxgr 5mo ago
      Do you have any benchmark details on the on-device Gemini models? I haven't found a lot of public information on these.

Sources for what? The pareto frontier of LLMs? How Google is pretty much on the line with most of their LLM products? Or this particular model? For the first two you need to look for size/cost vs. accuracy charts. There are tons of them floating around. For the latter there is not much official info except what you can infer by analyzing the weights.bin file that Chrome downloads. But it does mention Gemini in there, so it seems pretty obvious that it is from their proprietary line of models.

HumanOstrich 5mo ago
Sources for your claim that the model being downloaded to Android/Chrome is Gemini instead of Gemma. Other than downloading the bin file myself and analyzing it lol.
- sigmoid10 5mo ago
  How about Google itself? https://developer.chrome.com/docs/ai/prompt-api https://developer.chrome.com/docs/ai/prompt-api >With the Prompt API, you can send natural language requests to Gemini Nano in the browser.
  - deleted 5mo ago
    [deleted]
  - HumanOstrich 5mo ago
    Thanks. Looks like the current Gemini Nano is actually a separate model with the Gemma 3n architecture that has been distilled from Gemini 2.5 Flash[1]. Also, the next version of Gemini Nano will be based directly on Gemma 4 (so not distilled, not Gemini at all except for the name)[2]. So no, it's not a frontier model. Those don't run on your phone or in your browser. [1]: https://developer.android.com/blog/posts/ml-kit-s-prompt-api-unlock-custom-on-device-gemini-nano-experiences https://developer.android.com/blog/posts/ml-kit-s-prompt-api... [2]: https://android-developers.googleblog.com/2026/04/AI-Core-Developer-Preview.html https://android-developers.googleblog.com/2026/04/AI-Core-De...
    - sigmoid10 4mo ago
      Oh, now I see your problem. You confused the pareto frontier with the pure scale frontier. They are very much not the same. Also, distillation is how most of these smaller models are made from the biggest models. That process largely defines the frontier along most of the curve.
      - HumanOstrich 4mo ago
        > This also makes it the only open American frontier-level model right now. I'm not going to keep arguing with you. If you want to keep arguing, go to https://gemini.google.com/ https://gemini.google.com/. Gemini knows what a frontier model is and it knows that Gemini Nano is fundamentally different from the other Gemini models. For one, it uses the Gemma architecture. And the next version of Gemini Nano is built directly on Gemma 4. As for your original claim that I quoted, there are other "open American frontier-level models" by your definition. Like Gemma 4.
        sigmoid10 4mo ago
        I'm surprised how you try to evade the facts and even try to bring in Gemini in a vain attempt to support your argumentation, when a simple google search would have already pointed you at things like this: https://cloud.google.com/blog/topics/developers-practitioners/five-techniques-to-reach-the-efficient-frontier-of-llm-inference https://cloud.google.com/blog/topics/developers-practitioner... or this: https://arena.ai/leaderboard/text/overall/pareto https://arena.ai/leaderboard/text/overall/pareto The lines in these charts is literally what the frontier is on a technical level. None of what I said has any ambiguous terminology. This is common language in the field. Neither is the fact that google cares a lot about this. I don't see why you still feel the need to argue about any of this.
lxgr 5mo ago
Just because it's called Gemini doesn't mean that it's somehow automatically as comparable with the frontier of small models as well, does it?
- sigmoid10 5mo ago
  All Gemini models sit around the frontier, especially if you go to smaller sizes. Google is actually more invested into efficiency than size unlike some of the other big providers.
  - lxgr 5mo ago
    Do you have any benchmark details on the on-device Gemini models? I haven't found a lot of public information on these.