I'm actually liking 5.2 in Codex. It's able to take my instructions, do a good job at planning out the implementation, and will ask me relevant questions around interactions and functionality. It also gives me more tokens than Claude for the same price. Now, I'm trying to white label something that I made in Figma so my use case is a lot different from the average person on this site, but so far it's my go to and I don't see any reason at this time to switch.

Is there a "good enough" endgame for LLMs and AI where benchmarks stop mattering because end users don't notice or care? In such a scenario brand would matter more than the best tech, and OpenAI is way out in front in brand recognition.

"At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed"

This has been true for at least 4 months and yeah, based on how these things scale and also Google's capital + in-house hardware advantages, it's probably insurmountable.

Is there anything pointing to Brin having anything to do with Google’s turnaround in AI? I hear a lot of people saying this, but no one explaining why they do

> I start to believe OAI is very much behind

Kara Swisher recently compared OpenAI to Netscape.

GPT 5.2 is actually getting me better outputs than Opus 4.5 on very complex reviews (on high, I never use less) - but the speed makes Opus the default for 95% of use cases.

That's a quite sensationalized view.

Ghibli moment was only about half a year ago. At that moment, OpenAI was so far ahead in terms of image editing. Now it's behind for a few months and "it can't be reversed"?

i think the most important part of google vs openai is slowing usage of consumer LLMs. people focus on gemini's growth, but overall LLM MAUs and time spent is stabilizing. in aggregate it looks like a complete s-curve. you can kind of see it in the table in the link below but more obvious when you have the sensortower data for both MAUs and time spent.

the reason this matters is slowing velocity raises the risk of featurization, which undermines LLMs as a category in consumer. cost efficiency of the flash models reinforces this as google can embed LLM functionality into search (noting search-like is probably 50% of chatgpt usage per their july user study). i think model capability was saturated for the average consumer use case months ago, if not longer, so distribution is really what matters, and search dwarfs LLMs in this respect.

https://techcrunch.com/2025/12/05/chatgpts-user-growth-has-s...

OAI's latest image model outperforms Google's in LMArena in both image generation and image editing. So even though some people may prefer nano banana pro in their own anecdotal tests, the average person prefers GPT image 1.5 in blind evaluations.

https://lmarena.ai/leaderboard/text-to-image

https://lmarena.ai/leaderboard/image-edit

the trend I've seen is that none of these companies are behind in concept and theory, they are just spending longer intervals baking a more superior foundational model

so they get lapped a few times and then drop a fantastic new model out of nowhere

the same is going to happen to Google again, Anthropic again, OpenAI again, Meta again, etc

they're all shuffling the same talent around, its California, that's how it goes, the companies have the same institutional knowledge - at least regarding their consumer facing options

This is obviously trained on Pro 3 outputs for benchmaxxing.

Google has incredible tech. The problem is and always has been their products. Not only are they generally designed to be anti-consumer, but they go out of their way to make it as hard as possible. The debacle with Antigravity exfiltrating data is just one of countless.