3 ms·

At the current rate, open sourced models are expected to surpass cloud models within a couple years based on a study I read a couple days ago. Looking back at

At the current rate, open sourced models are expected to surpass cloud models within a couple years based on a study I read a couple days ago. Looking back at chatGPT and claude a couple years ago, very small Qwen models are basically equal in coding to what those cloud based models could do then. Also factoring in scaling laws, a 9b going to 18b is roughly a 40% increase, whereas 18b to 35b is 20%, I expect there will be a change of at least price in cloud based models. Adobe used to be $600 per month, then it became $20 when distribution scaled.

baxtr 6mo ago
While this might be true I’m worried about the hardware side of things. What if you have a good enough model but the cloud model providers are better in procuring hardware for interference?
- gleenn 6mo ago
  Local inference is definitely going to make more and more sense. Modern CPUs have all this amazing hardware well-optimized for inference purposes. I use a lot of web tools and see AI baked in and it feels weird. I want the smartness localized for speed and data security. I think and hope the industry points towards smart ai agents operating as locally as possible.
- zozbot234 6mo ago
  The cloud providers are probably better at procuring hardware for inference, but on prem users are better at repurposing hardware that they'd need anyway for their existing uses. In a world where AI compute is likely inherently scarce, it makes sense to rely on both.
- Gigachad 6mo ago
  You’ll be able to run the open models on any cloud at the cost of the hardware rental. While the closed models will try to mark up beyond the base cost.
- pheggs 6mo ago
  I personally believe that eventually manufacturers will want to sell more of their hardware and look for ways to sell hardware to consumers. isnt that situation quite similar to the days of early computers? I am for sure biased in hoping that will be the case
  - fireant 6mo ago
    Perhaps for some very specific capabilities such as TTS, translation, voice recognition and so on. But for general intelligence models, better hardware just directly allows better models and that doesn't seem to be changing any time soon.
    - pheggs 6mo ago
      I'm pretty sure that's not linear, so I personally expect the benefits of larger models to diminish. The question is at what point that's the case. I guess a lot of variables play into it, but it is possible that the benefits of running larger models will be too expensive for the little benefit they provide
Traubenfuchs 6mo ago
What were all the datacenters for???
- robinsonb5 6mo ago
  Those would be the Pork Futures Warehouse from Discworld.
sakjur 6mo ago
> Adobe used to be $600 per month, then it became $20 when distribution scaled. What product is this referring to? I haven't heard about Adobe having any offering that is quite that expensive?
great_psy 6mo ago
If you have a link to the study you read, please share it.
Marciplan 6mo ago
Adobe never costed $600 per month. They had Creative Suites upwards of $3000 but that was before SaaS
TeMPOraL 6mo ago
That makes no sense, though, and reeks of extrapolating a trend way beyond the conditions in which it is valid. The simple truth is, cloud models are always going to be strictly superior to open ones, simply because cloud model vendors can run those same open models too. And they still retain economies of scale and efficiency that operating large data centers full of specialized hardware, so at the very least they can always offer open models at price per token that's much less than anyone else's electricity bill for compute. But on top of that, they still have researchers working on models and everything around them; they can afford to put top engineers on keeping their harness always ahead of whatever is currently most popular on Github, etc.
- rubslopes 6mo ago
  I don't think the real-world evidence supports your argument... OpenAI and Anthropic have all of those advantages today, and Chinese models are reaching the same level. Clearly, the Chinese labs are doing something very right that is not directly related to infinite money.
  - TeMPOraL 6mo ago
    Doesn't change the argument. As long as the models are open, the big cloud providers have strict advantage, because even if some open model gets ahead, they can just serve it from their infra, and do it better than everyone else. This proves the strict inequality in my claim is preserved, everything beyond that is just debating the size of their advantage.
    - kelnos 6mo ago
      > As long as the models are open, the big cloud providers have strict advantage, because even if some open model gets ahead, they can just serve it from their infra Why would I want to use it, though? If, say, Anthropic were to serve a hypothetical Kimi K5.0 from their infra, seems like they'd keep their pricing where it is. If I can use that same model from kimi.com/Kimi Code, for less money (which seems like a safe bet in this scenario), then I wouldn't use Anthropic's offering. Even if Anthropic did lower prices, I doubt they'd be able to match kimi.com/Kimi Code. > ... and do it better than everyone else. Why would you assume this? That doesn't follow. "Better" has diminishing returns, and all of these companies have impressively scaled up already, and will continue to scale further in the coming years. And, regardless, I would absolutely use someone else's infra if it cost, say, 20% less, even if inference was a bit slower, or I hit rate limits more often (not usage limits, rate limits).
MintPaw 6mo ago
$600/mo? Do you mean $600 as a one time purchase for life? I've never heard of any Adobe plan that expensive.

baxtr 6mo ago

While this might be true I’m worried about the hardware side of things. What if you have a good enough model but the cloud model providers are better in procuring hardware for interference?

gleenn 6mo ago
Local inference is definitely going to make more and more sense. Modern CPUs have all this amazing hardware well-optimized for inference purposes. I use a lot of web tools and see AI baked in and it feels weird. I want the smartness localized for speed and data security. I think and hope the industry points towards smart ai agents operating as locally as possible.
zozbot234 6mo ago
The cloud providers are probably better at procuring hardware for inference, but on prem users are better at repurposing hardware that they'd need anyway for their existing uses. In a world where AI compute is likely inherently scarce, it makes sense to rely on both.
Gigachad 6mo ago
You’ll be able to run the open models on any cloud at the cost of the hardware rental. While the closed models will try to mark up beyond the base cost.
pheggs 6mo ago
I personally believe that eventually manufacturers will want to sell more of their hardware and look for ways to sell hardware to consumers. isnt that situation quite similar to the days of early computers? I am for sure biased in hoping that will be the case
- fireant 6mo ago
  Perhaps for some very specific capabilities such as TTS, translation, voice recognition and so on. But for general intelligence models, better hardware just directly allows better models and that doesn't seem to be changing any time soon.
  - pheggs 6mo ago
    I'm pretty sure that's not linear, so I personally expect the benefits of larger models to diminish. The question is at what point that's the case. I guess a lot of variables play into it, but it is possible that the benefits of running larger models will be too expensive for the little benefit they provide

Traubenfuchs 6mo ago

What were all the datacenters for???

robinsonb5 6mo ago
Those would be the Pork Futures Warehouse from Discworld.

sakjur 6mo ago

> Adobe used to be $600 per month, then it became $20 when distribution scaled. What product is this referring to? I haven't heard about Adobe having any offering that is quite that expensive?

great_psy 6mo ago

If you have a link to the study you read, please share it.

Marciplan 6mo ago

Adobe never costed $600 per month. They had Creative Suites upwards of $3000 but that was before SaaS

TeMPOraL 6mo ago

That makes no sense, though, and reeks of extrapolating a trend way beyond the conditions in which it is valid. The simple truth is, cloud models are always going to be strictly superior to open ones, simply because cloud model vendors can run those same open models too. And they still retain economies of scale and efficiency that operating large data centers full of specialized hardware, so at the very least they can always offer open models at price per token that's much less than anyone else's electricity bill for compute. But on top of that, they still have researchers working on models and everything around them; they can afford to put top engineers on keeping their harness always ahead of whatever is currently most popular on Github, etc.

rubslopes 6mo ago
I don't think the real-world evidence supports your argument... OpenAI and Anthropic have all of those advantages today, and Chinese models are reaching the same level. Clearly, the Chinese labs are doing something very right that is not directly related to infinite money.
- TeMPOraL 6mo ago
  Doesn't change the argument. As long as the models are open, the big cloud providers have strict advantage, because even if some open model gets ahead, they can just serve it from their infra, and do it better than everyone else. This proves the strict inequality in my claim is preserved, everything beyond that is just debating the size of their advantage.
  - kelnos 6mo ago
    > As long as the models are open, the big cloud providers have strict advantage, because even if some open model gets ahead, they can just serve it from their infra Why would I want to use it, though? If, say, Anthropic were to serve a hypothetical Kimi K5.0 from their infra, seems like they'd keep their pricing where it is. If I can use that same model from kimi.com/Kimi Code, for less money (which seems like a safe bet in this scenario), then I wouldn't use Anthropic's offering. Even if Anthropic did lower prices, I doubt they'd be able to match kimi.com/Kimi Code. > ... and do it better than everyone else. Why would you assume this? That doesn't follow. "Better" has diminishing returns, and all of these companies have impressively scaled up already, and will continue to scale further in the coming years. And, regardless, I would absolutely use someone else's infra if it cost, say, 20% less, even if inference was a bit slower, or I hit rate limits more often (not usage limits, rate limits).

MintPaw 6mo ago

$600/mo? Do you mean $600 as a one time purchase for life? I've never heard of any Adobe plan that expensive.