Several factual errors about the model here. The input modalities are listed as text only, but the headline feature is image support. The context length should be 1048576 (so should GLM-5.3's, also wrong on the charts).
Been using Luna exclusively since the price drop, and i've been very satified with all tasks from planning, writing code, and other agent tasks. (just change thinking level from low <-> ultra)
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btw, I did try out Ox Alpha, the coding feels good but still not way better for me to switch to it.
Luna is at a very compelling point on the price/performance curve.
I have found that sometimes a smaller model with max reasoning is actually more expensive than using the next tier model with a lower reasoning effort. It’s certainly faster.
> So how exactly is Anthropic and OpenAI ever going to pay back the trillions that they plan on spending?
It's really simple: if they truly get to human-level AI (or even superhuman AI), then money and debts no longer matter, since our current economic system will be obsolete. They are betting everything on this outcome.
I don't know if they will manage to do it before their debts have to be repaid, but considering the rate of acceleration in the past few months, there is a non-trivial chance that they will, IMHO. We will see.
1. they still have revenue though. it might not enough to cover all the r&d but it is surely enough to cover the hardware cost.
2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
so, surely chinese AI providers also lost money making new models, but they are not spending nearly as much as US ones.
>1. they still have revenue though. it might not enough to cover all the r&d but it is surely enough to cover the hardware cost.
>2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
Both arguments make it seem like there's a double standard for american vs chinese AI companies, where american labs are held up to strict standards for profitability, but chinese labs get a pass because [insert handwaving about how some aspect of chinese labs is different]. Let's do apples to apples comparisons here, what are both sides' run rates and revenue growth prospects?
>3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
Right, instead they're releasing their models for free so competitors can undercut them on inference. American labs' prospect of "there are open models 90% as good but cost less" might seem bad, but chinese labs' prospect of "there are companies offering the exact same models but aren't on the hook for r&d spend" seems even worse.
Literally nothing is known about how these companies are financed. The usual story is that Moonshot was chosen when 'Mythos' occasioned a huge state crisis. China is the ascended masters of insane amounts of capital poured into whatever the state takes into its head next.
just like there were mistrals, coheres, llamas, etc, there will be new deepseeks and moonshots if those ever flame out (worst case, given out at cost by google, meta, alibaba or etc)
OpenAI and Anthropic are already in a ~200bil hole from previous model iterations and are committing to trillions of additional spending
OpenAI spent more TBPN than kimi spent on training K3
They are by all accounts, not. Z.ai for instance is a public company according to wikipedia. Moonshot AI is private but all their investors are private companies. Alibaba, as we all know, is a massive publicly traded tech conglomerate.
Moreover even if we take the more charitable view that they're controlled by the CCP, and therefore will continue releasing models for free, that seems as questionable as the prospect that private investors will continue shoveling money into anthropic/openai.
China has "classroom game capitalism", where companies can play the game, but the teacher still has uncontested, absolute, unilateral control in everything and anything. All the parameters of the game are managed by the teacher, and the teacher is the one who creates the foundations for the direction they want the game to move in.
Don't forget, Jack Ma of "publicly owned" Alibaba, had to go into classroom time out after seemingly forgetting that its classroom capitalism and not real world capitalism.
Shoveling 70% less money into a money pit is still shoveling money into a money pit. Not to mention that at least openai/anthropic has better prospects of making back the money because their models are proprietary, and won't be cannibalized by other companies serving the exact same models.
Its more Google Amazon Meta Microsoft who are spending trillions. They will be fine. So will Anthropic and OpenAI. Nvidia will presumably survive. The losses are all the real estate interests and contractors and contributory hardware companies etc.
I expect they're going to fight each other to become the vendor of record for the government, and whoever wins will get bailed out. This is one area where they don't have to worry about competition from Chinese models.
I think most of us can see that the level of corruption we are seeing with the administration is quite historical. You can’t simply say “both administrations engaged in corruption” and consider the matter closed. Scale matters.
https://docs.z.ai/guides/vlm/glm-5.3-flash#model-api
- costs per task $0.05 vs $0.09
- speed 130 vs 88
- where GLM has only 5 more intelligence point: at this point few point is meaningless for most of models
https://artificialanalysis.ai/models/comparisons/glm-5-3-fla...
Been using Luna exclusively since the price drop, and i've been very satified with all tasks from planning, writing code, and other agent tasks. (just change thinking level from low <-> ultra)
---
btw, I did try out Ox Alpha, the coding feels good but still not way better for me to switch to it.
I have found that sometimes a smaller model with max reasoning is actually more expensive than using the next tier model with a lower reasoning effort. It’s certainly faster.
So Luna is competitive because a few weeks ago they did a 80% price drop?
Many here said that 80% drop was not a move against Anthropic but a move against chinese models and your comments indicate that's the case.
It's really simple: if they truly get to human-level AI (or even superhuman AI), then money and debts no longer matter, since our current economic system will be obsolete. They are betting everything on this outcome.
I don't know if they will manage to do it before their debts have to be repaid, but considering the rate of acceleration in the past few months, there is a non-trivial chance that they will, IMHO. We will see.
LLM has nothing to do with AGI.
2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
so, surely chinese AI providers also lost money making new models, but they are not spending nearly as much as US ones.
>2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
Both arguments make it seem like there's a double standard for american vs chinese AI companies, where american labs are held up to strict standards for profitability, but chinese labs get a pass because [insert handwaving about how some aspect of chinese labs is different]. Let's do apples to apples comparisons here, what are both sides' run rates and revenue growth prospects?
>3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
Right, instead they're releasing their models for free so competitors can undercut them on inference. American labs' prospect of "there are open models 90% as good but cost less" might seem bad, but chinese labs' prospect of "there are companies offering the exact same models but aren't on the hook for r&d spend" seems even worse.
OpenAI and Anthropic are already in a ~200bil hole from previous model iterations and are committing to trillions of additional spending
OpenAI spent more TBPN than kimi spent on training K3
They are by all accounts, not. Z.ai for instance is a public company according to wikipedia. Moonshot AI is private but all their investors are private companies. Alibaba, as we all know, is a massive publicly traded tech conglomerate.
Moreover even if we take the more charitable view that they're controlled by the CCP, and therefore will continue releasing models for free, that seems as questionable as the prospect that private investors will continue shoveling money into anthropic/openai.
Don't forget, Jack Ma of "publicly owned" Alibaba, had to go into classroom time out after seemingly forgetting that its classroom capitalism and not real world capitalism.
And the model isn't even shown in the speed bar chart just below. Such slop (the artificial intelligence website linked)