I believe it is much closer than you realize

https://huggingface.co/Qwen/Qwen-Image-2.1-Turbo (7B)

It may be, I didn't say otherwise. I said we don't know for a fact that this moment will come in the near future, so just handwaving that it's obvious is folly.

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verdverm an hour ago | parent [-]

There are already llms on phones now, they are being embedded / distributed by iOS and Android. You can find HN stories and comments about the struggle to disable or the joy of having them. Tons of Show HN about getting models to run on all sorts of devices, including phones

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jghn an hour ago | parent [-]

There's a difference between having "an llm" on a small device and having an llm of the class being discussed in this comment thread.

As I said, it may happen within a year. But maybe life takes a different direction. The person to whom I responded said "eventually", and yes, "eventually" it will happen. but that's not a useful time horizon to plan around because it could be a lot of things.

	▲	toomuchtodo an hour ago \| parent [-]
		If you build your app today to use an LLM API with credits so the economics works (or support existing LLM providers who can provide an API key for use within the app, to not expose the app to negative usage economics), but it has the capability to switch to a local API using existing known primitives, I think that is very useful in this context, no? The hard part is refining the UX, imho, while supporting pluggable LLM support on the backend. If the future never arrives of cheap on device inference, still works if you pay as you go and for those users willing to pay for their usage directly through their cloud inference provider of choice or through the app (unless the future is "cloud inference is unsustainable at consumer price points and on prem inference never arrives"). Just my two cents. This is fundamentally what Apple did with new Siri, powered by Gemini today. They will eventually flip the switch to an in house solution. Agree the wildcard that still remains is "can this be done on devices eventually?" https://www.apple.com/newsroom/2026/09/siri-ai-a-profoundly-... https://www.macrumors.com/2025/11/05/apple-siri-google-gemin... > Apple weighed using its own AI models for the LLM version of Siri , and also tested options from OpenAI and Anthropic, but it decided to go with Gemini after deciding Anthropic's fees were too high. Apple already has a partnership with Google for search results, with Google paying Apple around $20 billion per year to be the default search engine option on Apple devices. > Though Apple is planning to rely on Google AI for now, it plans to continue working on its own models and will transition to an in-house solution when its LLMs are capable enough. Apple is already working on a 1 trillion parameter cloud-based model that could be ready as soon as 2026. Apple is unlikely to publicize its arrangement with Google while it develops in-house models.