Gemini 4 Argon scores 32/35 in week-long test, but the app lags
A user who tested Gemini 4 Argon for seven days says it passed 32 of 35 tests and that Google may be able to build a top model, but a great model is not the same as a great AI product.
32/35 Gemini 4 Argon convinced me that Google may be capable of building one of the best models in the world. But a great model and a great AI product are not the same thing.
1/35 First, one important distinction: Gemini 4 Argon and the Gemini app are two very different things in my experience. The model impressed me a lot. The product around it still has major gaps.
7 days ago, around this time, I got early access to Gemini 4 Argon. Today that access ended. I spent the entire week testing it across long conversations, education, coding, tools, and real workflows. Here are my takeaways.
35/35 My final view after 7 days: Google may be able to win the model race. But if the Gemini app does not evolve just as quickly, it may still lose the user race. And thank you to Google for giving me early access to Argon. I genuinely appreciated the opportunity.
12/35 Now the bad part: Most of my complaints are not about Argon. They are about the Gemini product itself.
4/35 In several tests, Argon added small details I had not even thought to request. It felt less like a model trying to escape the task as quickly as possible, and more like one trying to produce a genuinely good result.
2/35 Argon does not feel like a simple continuation of older Google models. It feels genuinely new. Its tone, reasoning style, humor, examples, and overall behavior feel much more distinct than I expected.