That doesn't mean anything, it's just a name change. They're the same kind of unit.
And whatever accelerator you try to put into it, you're not running Gemini3 or GPT-5.1 on your laptop, not in any reasonable time frame.
And whatever accelerator you try to put into it, you're not running Gemini3 or GPT-5.1 on your laptop, not in any reasonable time frame.
I'm happy to say that LLM usage will only actually become properly integrated into background work flow when we have performant local models.
People are trying to madly monetise cloud LLMs before the inevitable rise of local only LLMs severely diminishes the market.
You dont need to run GPT5.1 to summerize a webpage. Models are small and specialized for different tasks.
And the examples being given of why you'd want AI in your browser are all general text comprehension and conversational discussions about that text, applied to whatever I may be browsing. It doesn't really get less specialized than that.
You also don't need Gemini3 or GPT anything running locally.
I've got Nemo 3 running on an iGPU on a shitty laptop with SO-DIMM memory, and it's good enough for my tasks that I have no use for cloud models.
Similarly, Granite 4 based models are even smaller, just a couple of gigabytes and are capable of automation tasks, summarization, translation, research etc someone might want in a browser.
Both do chain of reasoning / "thinking", both are fast, and once NPU support lands in runtimes, they can be offloaded on to more efficient hardware.
They certainly aren't perfect, but at least in my experience, fuzzy accuracy / stochastic inaccuracy is good enough for some tasks.