[HarHarVeryFunny]

My guess is that it's same base model as 5.5, but with additional post-training to improve and benchmaxx on a few things like that.

If they really thought it was competitive with Mythos/Fable across the board, then why wouldn't they release a broader set of benchmarks, and why price it day 1 at 1/2 the cost of Fable?

[famouswaffles]

>and why price it day 1 at 1/2 the cost of Fable?

Why would they price it the same as Fable it it doesn't cost the same as Fable ?

[HarHarVeryFunny]

That's half my point - Anthropic's remarks suggest that is Fable significantly bigger (hence more costly to run) than Opus, so it is priced accordingly, but GPT 5.6 priced the same as 5.5 is one datapoint that suggests they are the same size.

[famouswaffles]

Yeah...and why would being the same size mean anything ? This is par the course for Open AI. They've always been cheaper and likely smaller than Opus models even when they weren't much if any worse.

[HarHarVeryFunny]

> why would being the same size mean anything

Because these companies are still 100% scale-pilled, and each new generation of model is bigger than the previous one, even if active parameters (MoE) is growing slower than total parameters. There is also scaling in inference-time compute which adds to the cost just the same. Fable is rumored to use variable compute which will increase the cost for inputs that get routed for more compute.

Maybe as you suggest the OpenAI pricing is unrelated to size/cost, but if so it seems a very aggressive move given that models that cost more to train and run need to generate more revenue to be profitable.

[famouswaffles]

I'm not saying Open AI pricing is entirely unrelated to size/cost. I'm saying why are we assuming that OpenAI is serving say OAI-Opus but at half the price of Anthropic when they could just be serving GPT-5.x which is genuinely near half the cost of Opus at scale.

The official API output tokens cost of GLM-5.2 is like a third of Gemini-3.1-Pro. The model is Open weights so we know it's not just a ploy to grab users at the cost of bleeding money. You can actually serve the model profitably at similar prices.

They have near a billion consumer users every week. Compute efficiency at scale would be at the forefront of any training effort. It makes a lot more sense to me that they have more compute efficient models (even with the scaling) than Anthropic rather than just serving Opus/Fable at half the costs Anthropic are incurring.