41–50 of 527 posts
What is wrong with OpenAI? The naming of their models seems like it is intentionally confusing - maybe to distract from lack of progress? Honestly, I have no idea which model to use for simply everyday tasks anymore.
Surprisingly, they didn't provide a comparison to Sonnet 3.7 or Gemini Pro 2.5—probably because, while both are impressive, they're only slightly better by comparison. Lets see what the pricing looks like.
It's pretty frustrating to see a press release with "Try on ChatGPT" and then not see the models available even though I'm paying them $200/mo.
As a consumer, it is so exhausting keeping up with what model I should or can be using for the task I want to accomplish.
• o3 Pricing:
- Input: $10.00
- Cached Input: $2.50
- Output: $40.00
- Input: $15.00
- Cached Input: $7.50
- Output: $60.00
As a consumer, it is so exhausting keeping up with what model I should or can be using for the task I want to accomplish.
It's becoming a bit like iphone 3, 4... 13, 25... Ok they are all phones that run apps and have a camera. I'm not an "AI power user", but I do talk to ChatGPT + Grok for daily tasks and use copilot. The big step function happened when they could search the web but not much else has changed in my limited experience.
It confers to the speaker confirmation they're absolutely right - names are arbitrary.
While also politely, implicitly, pointing out the core issue is it doesn't matter to you --- which is fine! --- but it may just be contributing to dull conversation to be the 10th person to say as much.
It's pretty frustrating to see a press release with "Try on ChatGPT" and then not see the models available even though I'm paying them $200/mo.
"ChatGPT Plus, Pro, and Team users will see o3, o4-mini, and o4-mini-high in the model selector starting today, replacing o1, o3‑mini, and o3‑mini‑high."
with rate limits unchanged
{Size}-{Quarter/Year}-{Speed/Accuracy}-{Specialty}
Where:
* Size is XS/S/M/L/XL/XXL to indicate overall capability level
* Quarter/Year like Q2-25
* Speed/Accuracy indicated as Fast/Balanced/Precise
* Optional specialty tag like Code/Vision/Science/etc
Example model names:
* L-Q2-25-Fast-Code (Large model from Q2 2025, optimized for speed, specializes in coding)
* M-Q4-24-Balanced (Medium model from Q4 2024, balanced speed/accuracy)
What is wrong with OpenAI? The naming of their models seems like it is intentionally confusing - maybe to distract from lack of progress? Honestly, I have no idea which model to use for simply everyday tasks anymore.