Not sure who would use Terra anymore. Pair Luna High/Xhigh with Sol Medium and that's your power stack
Advancing the price-performance frontier with GPT‑5.6
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Re: Advancing the price-performance frontier with GPT‑5.6
#12> GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less Looks like the Chinese models are really making a dent. Having 3 different price categories with the "most affordable" one still costing more than GLM 5.2 never made sense.
It all comes back to electricity cost. China has cheaper electricity so as long as China keeps pace there is no way for American companies to undercut them. Each boolean operation in China is cheaper than the one in America.
> China: Household rates average around $0.08 / kWh (¥0.53/kWh).
vs
> US: Household rates average around $0.16 / kWh, though regional variation is massive—ranging from ~$0.10/kWh in low-cost states (like Washington or Louisiana) to $0.30–$0.45+/kWh in high-cost areas like California or Hawaii.
Re: Advancing the price-performance frontier with GPT‑5.6
#13This is awesome. Luna is a pretty great model on xhigh.
Re: Advancing the price-performance frontier with GPT‑5.6
#14> 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.
Re: Advancing the price-performance frontier with GPT‑5.6
#15> 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
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.
Re: Advancing the price-performance frontier with GPT‑5.6
#16Model 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.
it is really hard to know upfront if you have fuzzy task. sometimes i would choose a cheaper model and it will spin and spin with bad outputs ending up costing more had i chosen a more capable model.
Re: Advancing the price-performance frontier with GPT‑5.6
#17> 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…
~2 years ago gemini2.5 helped write better kernes for itself and (only) reached 1% efficiency gains. Today we're at 20%.
Re: Advancing the price-performance frontier with GPT‑5.6
#18> GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less Looks like the Chinese models are really making a dent. Having 3 different price categories with the "most affordable" one still costing more than GLM 5.2 never made sense.
I thought the chinese models were cheaper per token, but about the same or more expensive on tasks because they used more tokens for reasoning. Cutting even further, seems like a really big leap.
Re: Advancing the price-performance frontier with GPT‑5.6
#19This is awesome. I’ve recently set up my opencode to use 5.6 terra for my main agent, who delegates work to a 5.6 Luna coder agent. So far it seems to work well, and reduce costs a lot. With this price reduction, it will work a whole lot better. Perhaps I can get my github copilot quota to last the whole month now.
Re: Advancing the price-performance frontier with GPT‑5.6
#20Not sure who would use Terra anymore. Pair Luna High/Xhigh with Sol Medium and that's your power stack
Sounds reasonable. Is there a good benchmark on which make this decision?