You can get the Google pro subscription (forget what they call it) that's ordinarily $20/mo for free right now (1 month free; can cancel whenever), which gives unlimited Gemini 2.5 Pro access.
I hope you appreciate just how crazy this sentence sounds, even in an age when this is normalised.
You're holding it wrong. You need to utter the right series of incantations to get some semblance of truth.
What, you used the model that was SOTA one week ago? Big mistake, that explains why.
You need to use this SOTA model that came out one day ago instead. That model definitely wasn't trained to overfit the week-old benchmarks and dismiss the naysayers. Look, a pelican!
What? You haven't verified your phone number and completed a video facial scan and passed a background check? You're NGMI.
Love this reference :)
- o3 is the bestest and my go-to, but its strength comes from it combining reasoning with search - it's the one model you can count on finding things out for you instead of going off vibe and training data;
- GPT 4.5 feels the smartest, but also has tight usage limits and doesn't do search like o3 does; I use it when I need something creative done, or switch to it mid-conversation to have it reason off an already primed context;
- o4-mini / o4-mini-hard - data transformation, coding stuff that doesn't require looking things up - especially when o3 looked stuff up already, and now I just need ChatGPT to apply it into code/diagrams;
- gpt-4o - only for image generation, and begrudgingly when I run out of quota on GPT 4.5
o3 has been my default starting model for months now; most of my queries generally benefit from having a model that does autonomous reasoning+search. Agentic coding stuff, that I push to Claude Code now.
Unlike Catholic saints, ChatGPT models actually exhibit these properties in directly observable and measurable way. I wrote how I decide which model to use for actual tasks, not which saint to pray to.
> actually exhibit these properties in directly observable and measurable way
Well but do they? I don't mean your vibes, and I also don't mean cooked-up benchmarks. For example: https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
Or perhaps you stop being obtuse. There's no causal connection between "using saints for actual tasks" and the outcomes, which is why we call this religion. In contrast, you can see the cause-and-effect relationship directly and immediately with LLMs - all it takes is going to chatgpt.com or claude.ai, typing in a query, and observing the result.
> Well but do they? I don't mean your vibes, and I also don't mean cooked-up benchmarks.
Do read the study itself, specifically the parts where the authors spell out specifically what is or isn't being measured here.
You may not like but it's what it is.
Still, it's not what you're saying. Vibes are present, too, but so are concrete effects like one-off utilities conjured in 2 minutes of prompting instead of 10 minutes of searching or 1 hour of coding, or research questions answered swiftly (and answers verified by me), that I normally wouldn't consider tackling due to up-front effort being greater than my discretionary time. And so on.
This is not vibes, but hard, empirical evidence, immediately retrievable as it just accumulates in the chat history, so I can always go back to check if I wasn't misremembering things.
There's a silver lining in this, though: none of that is any kind of deep expertise, so there's no need for up-front investment. Just start using a tool and pay attention, and you'll pick up on those things in no time.