> 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.

> 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 don't know how much of Anthropic's inference capacity that is (presumably a small fraction, since they were operating on top of AWS and other providers before the SpaceX deal.)

I've not seen any numbers that hint at OpenAI's per-month inference bill, but surely that has to be in the multiple billions of dollars as well.

So 20% is a really, really big deal.

Making Luna, which was already very cheap and extremely capable, 5x cheaper is crazy. I use Sol at work but Luna at home, and while there's definitely a difference, it doesn't feel like night-and-day. After a year of ever-increasing prices it suddenly feels (between this, Kimi K3, GLM 5.2) that prices are falling again.

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.

They don't mention Grok at all.

Not sure who would use Terra anymore. Pair Luna High/Xhigh with Sol Medium and that's your power stack

This is awesome. Luna is a pretty great model on xhigh.

> 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 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.

80% price cut for luna is a very aggressive pricing move

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!)

This is one of the things OpenAI has been focused on for an year or so that led to the doomed autoswitcher in ChatGPT .com (switching models based on estimated task complexity) that was quickly reverted

Whereas Google with Gemini 3.x, Anthropic with Fable etc are happy to just go for 'big model with dense params'

It's hard to guess from the outside of course but just this kind of talking points focus on GPU efficacy is what we see from OpenAI and Chinese open source labs more often than from Anthropic or Google Deepmind and this benchmark chart seems to concur

This feels like the dialup->broadband transition to me.

I was already a huge proponent of Luna for things like deep research. Being able to run 5x more for the same cost is simply bananas. We are already running 10 parallel agents for hypothesis generation. I cannot imagine 50. The statistics become much more interesting & powerful when you can run so many samples of the exact same prompt+model without breaking the bank.

Cool.. but impossible to gauge if this has to do with algorithmic optimizations; undercutting competitors; geopolitics; declining demand; the recent stock sellof; any other of the myriad of possibilities. OpenAI has not shown themselves to be an actor that you take at their word.

One hopes that, maybe one day, we'll have completely transparent inference profit, calculable carbon footprint per token, and no more predatory market-capture tactics. Maybe one day.

It is going to be remarkable how many question will be answered when we finally get to see the S-1.

Basically lunar at extra level can cover all use cases scenarios other than those requiring opus up. Goodbye sonnet and haiku

Looks like I might have a reason to use something other than Deepseek V4 Flash.

“Half the money I spend on advertising is wasted; the trouble is I don't know which half.” -John Wanamaker

This applies even more strongly to model choosing. I know for a fact that majority of my work doesn't require a very strong model, but separating the trivial and non-trivial tasks is a famously hard problem (if at all decidable).

I generally just check the Price/Performance graph on Openrouter: https://openrouter.ai/rankings#performance#benchmarks. Activate the "Show Pareto" toggle on the right.

I was still using GLM-5.2 in my personal projects, but this just made Luna a very easy choice.

What are your use case for these? I’m manly interested in coding where more capability is better - give me a 10x model at 10x the price and I’ll take it. A worse model at very low cost has no appeal to me. At-least not for coding. Translation maybe? OCR?

Those prices on luna are killer.

Haiku was already in a ditch.

But this is coming straight for the jugular of a ton of models on openrouter.

It would appear that rolling my own Anthropic-free harness / serving stack with a closed-weight carve out for Codex models is an absolute win.

Might just resub. Will experiment with Luna next sessions. 5 h window is not working very well for me. But if I can drop down to Luna at 20-30 % left and comfortably ride out the wave then.. that might just work.

Didn't expect that. Luna pricing is crazy now. I don't think there is anything on the market that competes at this price-performance point.

For our production app, OpenAI clearly is the best provider now. Their API is very reliable and has many nice features. The price-performance of the model lineup is incredible. We used open weights model via Fireworks for a long time (e.g. Kimi K2.5). Fireworks is a great provider but we still ran into issues here and there (Same with Anthropic and Google). OpenAI just works, is fast and in my view has a better price-performance ratio across almost all levels of intelligence.

Seems like they cut the tiers(GPT-5.6 Luna) where GLM and Kimi compete and still held margin for their frontier models

80% less for Luna is absolutely crazy, in my opinion we may reach a point in the next year where powerful models on the API could potentially be cheaper than subscriptions. Compute just keeps decreasing in price.

It says Luna is fastest, but doesn't it take way more steps to get the same job done?

https://deepswe.datacurve.ai/ - (See the Agent Steps view)

Or is the output speed so much higher that it cancels out?

I don't see a lot of benchmarks that record actual time. But on AA, Sol on Low beats Luna on High for Time Per Task.

While I can't deny this is a huge technological result, and it's laudable they reduced the price because of it, 80% is really a lot. I can't help but wonder, is this because of the model's capabilities, or was the initial system just really sloppy? The public will probably never know the details

We swapped an internal system from gpt-5-mini to gpt-5.6-luna and saw no benefit but 4x cost. Sufficed to say: we swapped back to gpt-5-mini.

I would pay significantly more to use these models if there was a legal contract that guaranteed they weren't ever terfing them and some way to prove that.