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Comment by pjerem | Hacker News Reader

The news is not in the way to compare models, it’s that Kimi K2.6 (and I’d add Deepseek v4 Pro) are more or less equivalent to Opus and that’s already pretty big.

They are open source and cost waaaay less per token than American models.

I’m using them right now on the $20 Ollama cloud plan and I can actually work with them on my side projects without reaching the limits too much. With Claude Pro $20 plan my usage can barely survive one or two prompts.

And I choose Ollama cloud just because their CLI is convenient to use but their are a lot of other providers for those models so you aren’t even stuck with shitty conditions and usage rules.

To me that’s a pretty bad thing for American economy.

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Or maybe it is a pretty good thing for the American economy that you can get AI at cost rather than monopoly pricing.

You know, for the rest of the economy that is not big tech.

It's not good for current administration. The American AI growth is only thing that keeps the GDP not looking terrible.

And investor pumping money in US AI circular money flow just makes innovation everywhere else slower. If not for the GPU/Memory drought running stuff locally (or just in competition cloud) would be far cheaper

> It's not good for current administration

I don't know where to begin if you're leading with that. Anything approaching reality is not good for the current administration.

That is the very reason the open source models exist. Prestige and soft power to influence interest away from American models and hopefully slow down their progress.

DeepSeek and other Chinese model makers are massively accelerating progress in AI not slowing it down. They're the only ones who still come up with real technical innovations while the proprietary model makers are stagnating.

I'm as happy to see cheap open weight models any anyone is, and I'm in Europe and certainly not cheering the US on, but that's a bunch of unfounded hyperbole you just said.

You should read the research papers that come out with Deepseek releases. There is a reason why the first Deepseek release briefly caused existential panic.

I did not and am not inclined to invest the time to do so.

But I did read some second hand reports that what was new and exciting was that they found some really good performance optimizations. The thing about deekseek publishing this is that now everyone has this.

Or did I miss something?

from the "DeepSeek is a ploy to undermine usamerican models' duopoly" theory's perspective, "now everyone has this" helps them achieve this goal more efficiently.

especially if it's something that the major companies had already stumbled upon (something equivalent to) and regarded as a trade secret.

> The thing about deekseek publishing this is that now everyone has this.

It sounds like you're agreeing with upstream comment then!

>> DeepSeek and other Chinese model makers are massively accelerating progress in AI not slowing it down

>> DeepSeek and other Chinese model makers are massively accelerating progress in AI... They're the only ones who still come up with real technical innovations.

> that's a bunch of unfounded hyperbole you just said.

Calling the quote on top "unfounded hyperbole" betrays lack of knowledge and awareness about the subject. Keep in mind that when we talk about real technical innovations, we have in mind published research - not closed or hidden models, some of which we know only from hype but cannot even test. A cursory look at said research reveals more Chinese names than I can count.

Deepseek did introduce real technical innovations, they're in their papers, and there was plenty of talk about another "Sputnik moment" when their first model appeared. If you don't know what that means - it's the moment when the industry mobilizes to "accelerate progress" due to the unexpected appearance of strong competition.

There's a lot more to be said, but it wouldn't do much good to a person who's not following the trends.

Can you name some tangible AI idea that came out of Chinese labs?

I can name thousands that came out western universities.

I see a lot of rhetoric that only the Chinese labs are contributing to AI while companies like Google and Microsoft are still pulishing their research.

Unfortunately the domain of scientific papers is cluttered with AI slop but still occasional serious paper that i find are from western labs particularly Google Research or Microsoft Research

Any of DeepSeek's recent papers which are more about efficiency and that's how their inference costs can be so low.

Oh please https://github.com/deepseek-ai

It doesn't mean only Chinese companies are contributing. Take TurboQuant, a serious theoretical paper not just GPU optimization, it was google research as the original transformers as MoE and many other techniques we use daily in deep learning as for libraries like TensorFlow which were pivotal to fast development of AI

Bit of a strawman, isn’t it.

That is a petty big assumption (aka bullshit) unless you have direct insight the inner workings of the big US labs. Just because it isn’t published doesn’t mean that innovation is not happening.

That's an unfalsifiable assertion with no evidence to support it, while all the visible evidence we do have points to stagnation and merely incremental pushes among the big proprietary model makers. Even Claude Mythos, which was 'teased' to the public but not released, is reportedly mostly a scaled-up model that takes massive compute resources to run (and lengthy agentic loops to achieve its reported results in computer security). The polar opposite to what the Chinese labs are releasing now.

So no insight and just going off blogposts and YouTube huh. Pot kettle calling each other black etc.

Sam Altman certainly got all lovey-dovey and less arrogant after DeepSeek came into prominence at most 3-6 month gap, if there was something mind blowing, Sam would’ve gotten money out of Apple and the same thing applies to Google if they had something mind blowing, they would’ve gotten more than a $1 billion refund neither happened. The bubble is near…

I am using both on OpenCode Go plan and they're pretty good, but I would say still not at the same level at GPT-5.5 in my experience, I don't know about Opus.

On a different note, is Ollama cloud good?

> is Ollama cloud good?

I'd say they have reliability issues but for the price it's worth it.

I like that usage isn't measured per token but per computation time, which means that you get more usage when models become more efficient.

They are no way as good as Opus yet. But Sonnet, yes. Using all in real life.

I appreciate your reply but you are completely glossing over his point about how head to head model evals are useless lmao

> for American economy.

There is more to American economy than big tech.

And that's precisely why this has started: https://www.wired.com/story/super-pac-backed-by-openai-and-p...

>There is more to American economy than big tech.

Most of the stock market valuation is big-tech, and most of people's retirements are the stock market, so... if the AI bubble bursts a lot of the US will be affected.

I do not know why this is downvoted. This is true.

Agreed. I upvoted.

>Most of the stock market valuation is big-tech

Which is why most of it is a bubble

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