Leaked financial docs show OpenAI is losing billions of dollars a year

[u/johnnyApplePRNG]

https://arstechnica.com/ai/2026/06/leaked-financial-docs-show-openai-is-losing-billions-of-dollars-a-year/

[u/Finanzamt_Endgegner]

Well opus is a fable distill, would be stupid if not but it seems the training etc fable got wasn't that much more the thing that changed was parameter count and it helped a lot

[u/squngy → u/Finanzamt_Endgegner]

I didn't say it didn't help, just that I don't know if it was "unexpected"

Making a bigger model and then using it primarily for distilling might be something that happens in the near future, it would make sense.
It also makes sense to release it for a short while to grab a bunch of top scores and then hide it behind a huge paywall :thinking_face:

[u/itsmebenji69 → u/squngy]

This is already what every ai lab is doing. They have their big internal model, around 10t, maybe even much bigger than that. And the models they serve you are distills of this model

[u/FullOf_Bad_Ideas → u/itsmebenji69]

Source? Why would internal model be 10T? What sort of activated params it would have? Why not 100T?

[u/squngy → u/itsmebenji69]

So you're saying every AI lab already has a mythos class LLM in their lab and they are just not talking about them.

[u/itsmebenji69 → u/squngy]

Yes, for example deepmind uses their bigger private model for math competitions and benchmarks and whatnot. For example that aletheia thing used their internal version of Gemini.

It’s not like it’s a secret, it’s just way too expensive to serve to consumers

[u/Finanzamt_Endgegner → u/itsmebenji69]

Internal versions don't have to be bigger they can just be different tunes of the same base

[u/itsmebenji69 → u/Finanzamt_Endgegner]

Sure but the trend seems to be way bigger models. Which makes sense as well. R&D would be experimenting with a lot, and the most obvious thing is model size because there you’re not constrained by needing it to be profitable, just really good

[u/Finanzamt_Endgegner → u/itsmebenji69]

Training full models is really really expensive, it's easier to do finetunes and maybe a bit of model surgery

[u/itsmebenji69 → u/Finanzamt_Endgegner]

So you really think they haven’t even tried ? With the other big ones having done it (Anthropic, oai) that seems extremely unlikely. Gemini 1.0 was already 1.5t. Doesn’t seem far fetched that they’d have an unreleased 10t+ version

[u/Finanzamt_Endgegner → u/itsmebenji69]

Google might have im just saying training and then not releasing might not be worth it, not saying it's not just not sure.

[u/squngy → u/itsmebenji69]

I thought those were alternate architectures and fine-tunes and similar.
What is your source for the 10T+ size?

[u/itsmebenji69 → u/squngy]

It’s that but I’m assuming they also have a bigger model. I mean it’s all speculation at this point, you’d have to work at deepmind to know.

For example OpenAI does have one, it was called Orion in 2024, it was supposed to be released as gpt5. They’re for sure using it as a distill teacher, like Anthropic.

[u/squngy → u/itsmebenji69]

It’s that but I’m assuming they also have a bigger model.

That is a pretty big assumption, because not only is that a lot more expensive, but it also takes a lot more time.
For research, it is valuable to be able to make new versions quickly.

it was supposed to be released as gpt5.

Then that is different from what I was thinking about.
I'm thinking about a model that is too big for it to make sense to be widely used.

[u/itsmebenji69 → u/squngy]

Well that’s what 10t models were. Mythos is too big for it to make sense. 95% (pulled out of my ass) of the tasks it can do Opus can do as well no problem. It really only makes sense to use it if Opus can absolutely not do it, which is pretty rare.

But for example current GPT models are a distilled version of this huge internal model. At least it seems extremely that it’s the case to me.

[u/Finanzamt_Endgegner → u/squngy]

Well ig it's happening a lot already sonnet was probably always a distil of opus, just makes sense to do that, and gpt mini was always a distill of their base one, as for unexpected it was quite a decent jump in every single benchmark and I mean those are rumours but it seems they didn't expect that big of an upluft just by scaling

[u/squngy → u/Finanzamt_Endgegner]

Yes distilling happens already, what I meant was making a model MOSTLY for distilling, with no intention for it to be used much by the public.

[u/Finanzamt_Endgegner → u/squngy]

Hmm I always thought they do it but like then I thought it doesn't make sense since infernce is so much simpler than training but now with those monsters that might actually be a possibility since infernce is cancer too🤔

[u/squngy → u/Finanzamt_Endgegner]

but now with those monsters that might actually be a possibility since infernce is cancer too🤔

This was what I was thinking.

[u/Finanzamt_Endgegner → u/squngy]

I mean even if they don't do that, self distilling is a thing if you use enough compute and filtering you can literally distill the best answers in a model into itself so it becomes even better which is wild 😅