Why doesn't OpenAI include comparisons to other models anymore?
Because their main competition (Google and Anthropic) have caught up and even started to surpass them, and comparisons would simply drive it home.
GPT-5.2
181–190 of 1001 posts
Re: GPT-5.2
#182Earlier quoted context omitted.
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Not sure what you mean, Altman does that fake-humility thing all the time. It's a marketing trick; show honesty in areas that don't have much business impact so the public will trust you when you stretch the truth in areas that do (AGI cough ).
I'm confident that GP is good faithed though. Maybe I am falling for it. Who knows? It doesn't really matter, I just wanted to be nice to the guy. It takes some balls posting as OpenAi employee here, and I wish we heard from them more often, as I am pretty sure all of them lurk around.
Re: GPT-5.2
#183> Unlike the previous GPT-5.1 model, GPT-5.2 has new features for managing what the model "knows" and "remembers to improve accuracy.
Dumb nit, but why not put your own press release through your model to prevent basic things like missing quote marks? Reminds me of that time an OAI released wildly inaccurate copy/pasted bar charts.
Re: GPT-5.2
#184Earlier quoted context omitted.
I'm quite sad about the S-curve hitting us hard in the transformers. For a short period, we had the excitement of "ooh if GPT-3.5 is so good, GPT-4 is going to be amazing! ooh GPT-4 has sparks of AGI!" But now we're back to version inflation for inconsequential gains.
Take this all with a grain of salt as it's hearsay: From what I understand, nobody has done any real scaling since the GPT-4 era. 4.5 was a bit larger than 4, but not as much as the orders of magnitude difference between 3 and 4, and 5 is smaller than 4.5. Google and Anthropic haven't gone substantially bigger than GPT-4 either. Improvements since 4 are almost entirely from reasoning and RL. In 2026 or 2027, we shoul…
4.5 is widely believed to be an order of magnitude larger than GPT-4, as reflected in the API inference cost. The problem is the quantity of parameters you can fit in the memory of one GPU. Pretty much every large GPT model from 4 onwards has been mixture of experts, but for a 10 trillion parameter scale model, you'd be talking a lot of experts and a lot of inter-GPU communication.
With FP4 in the Blackwell GPUs, it should become much more practical to run a model of that size at the deployment roll-out of GPT-5.x. We're just going to have to wait for the GBx00 systems to be physically deployed at scale.
Re: GPT-5.2
#185Slight increase in model cost, but looks like benefits across the board to match. gpt-5.2 $1.75 $0.175 $14.00 gpt-5.1 $1.25 $0.125 $10.00
40% increase is not "slight."
Not the OP, but I think "slight" here is in relation to Anthropic and Google. Claude Opus 4.5 comes at $25/MT (million tokens), Sonnet 4.5 at $22.5/MT, and Gemini 3 at $18/MT. GPT 5.2 at $14/MT is still the cheapest.
Re: GPT-5.2
#186Re: GPT-5.2
#187Given the price increase and speculation that GPT 5 is a MoE model, I'm wondering if they're simply "turning up the good stuff" without making significant changes under the hood.
Re: GPT-5.2
#188Re: GPT-5.2
#189Given the price increase and speculation that GPT 5 is a MoE model, I'm wondering if they're simply "turning up the good stuff" without making significant changes under the hood.
GPT 4o was an MoE model as well.
Re: GPT-5.2
#190Is it me, or did it still get at least three placements of components (RAM and PCIe slots, plus it's DisplayPort and not HDMI) in the motherboard image[0] completely wrong? Why would they use that as a promotional image? 0: https://images.ctfassets.net/kftzwdyauwt9/6lyujQxhZDnOMruN3f...
Yep, the point we wanted to make here is that GPT-5.2's vision is better, not perfect. Cherrypicking a perfect output would actually mislead readers, and that wasn't our intent.
That would be a laudable goal, but I feel like it's contradicted by the text:
> Even on a low-quality image, GPT‑5.2 identifies the main regions and places boxes that roughly match the true locations of each component
I would not consider it to have "identified the main regions" or to have "roughly matched the true locations" when ~1/3 of the boxes have incorrect labels. The remark "even on a low-quality image" is not helping either.
Edit: credit where credit is due, the recently-added disclaimer is nice:
> Both models make clear mistakes, but GPT‑5.2 shows better comprehension of the image.