In addition to GrapheneOS changes, there have been some other changes to fill in the missing gaps. Similar to thinking about where the food you eat comes from, it's a useful exercise to learn about where the features you use come from. I talked about this in a past post, but the short version is: it's either AOSP, Google's apps, or the Pixel ROM. Since my initial GrapheneOS post, a few more missing features have been filled in.
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The workflow begins with identifying the queries you want to track. These are essentially "AIO keywords"—questions that people might ask AI models where your content should ideally appear in the answer. Unlike traditional SEO keywords, which are often short phrases, AIO queries tend to be longer, more conversational questions that reflect how people actually talk to AI assistants.
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在学术评测 GPQA Diamond 上得分 86.9%，多模态理解 MMMU Pro 上达到 76.8%。这两个数字不只是「在同档位里还不错」，而是直接超过了体量更大的 Gemini 2.5 Flash。