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> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.
This is very likely priced below recovering the cost of the hardware but still above operating expenses.
> The kernel work helped reduce the end-to-end cost of serving the model by 20%, while its experiments increased token-generation efficiency by more than 15%. If the cost of serving GPT-5.6 just dropped by 20%, does that add up to literally billions of dollars in savings per month? We know Anthropic spend $1.25 billion renting inference capacity from SpaceX (in two Colossus datacenters) from the SpaceX IPO, but we do…
imagine writing that on your resume > reduced inference cost by 20 percent saving company x billion dollars per month
They don't mention Grok at all.
> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.
They don't mention Grok at all.
> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.
Model segmentation & distillation like this that asks the consumers to pick exactly which version of the algorithm will solve their problem is evidence for lack of intelligence instead of its presence.
Now, if cost is your concern, then that’s a problem in all of computing. Hence why I’m sending you short plain text messages using an iPhone with a many-core CPU and gigabytes of RAM.
Earlier quoted context omitted.
imagine writing that on your resume > reduced inference cost by 20 percent saving company x billion dollars per month
In this case, and I don't mean this critically, I guess it would technically be, "Instructed model to find efficiencies... reducing inference cost by 20% saving company x billion dollars per month." I have no doubt that further work was required to enable this, but it's still very cool to be possible to say that.
> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.
To be fair we don't really know in terms of prices what's real and what's just investor subsidised attempts at market capture at this point. It could well be OpenAI's attempt to drown Anthropic while they've got the halo product if they feel they've got deeper pockets.
makes it by far the best choice for most workloads that do not need bleeding edge intelligence (reminder: luna can be comparable to opus 5!)