alt Hacker NewsI was wondering how does Anthropic and likes keep competitive when Opus is ($5 / $25) 5x times more expensive compared to Kimi K2.6 ($0.7 / $3.4) or other Chinese models, while being only marginally better.
My theory is that US enterprise just can't send data to Chinese and that's understandable, but is that "the moat"?
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API token price is one thing, but subscriptions on Claude are a good value. Weirdly everyone says that Claude subscriptions are subsidized because of the API price, even though (1) no one actually knows Claude's cost of inference, and (2) Chinese providers are also able to provide cheap inference, so why do they think Claude can't?
I also wonder if Enterprises have deals for other API pricing that is not posted publicly, so all we see is a high API sticker price.
I think the perception is that it is not 'only marginally better'; whether or not you specifically agree that perceived quality gap lets them differentiate on price.
I'd further say that there are probably enough rational actors running evals out there that the marginally better is not pure vibes for the cases where people are spending lots of money, but I only have direct line of sight to some of those eval suites. Maybe everyone is irrational and anthropic is exploiting that!
I think most people who've tried them both would tell you Anthropic's models are more than marginally better than Kimi. Kimi and the other open source models may score well on SWE-bench or whatever but the gap is noticeable IMHO once you actually try to use them.
I reckon right now the Enterprise concern is more FOMO around the AI wave and how to retrain or replace up to hundreds of thousands of employees. I don't think cost is the main concern right now.
But if AI doesn't lead quickly to vast large scale replacement of workers as promised, I could definitely see the C-suits and their gaggle of consultants starting to ask questions about token pricing.
Your question relies on the premise that Chinese companies continue releasing free models. What's "the moat" for them continuing to do that?
I want Opus to be only marginally better, but I do mostly research engineering and its ability to not fuck up my projects is absent. Every time my credits lapse I let kimi and composer2.5 have some play and it’s basically just an excuse for me to keep playing computer because when the oai/ant credits refresh I always need to spend hours recovering from the other models either misconceptions or boneheaded eng practices. Even when I only let it touch my web games…
I think none of them having a defacto and high quality English focused cli is a big part of it. None of the Chinese models I've tried have worked well in opensource cli's. Granted, I've only tried a few, but still...
> My theory is that US enterprise just can't send data to Chinese
Lots of US providers are hosting these “open source” models so doubt that’s the problem.
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The moat right now is model performance and what that means for how many tokens and additional time you spend.
I say this as a relatively frequent user of Kimi models and generally a big fan. But on not-yet-gamed benchmarks like DeepSWE, Kimi K2.6 is beaten soundly by Claude Sonnet 4.6 ($3 / $15) and even slightly by GPT 5.4 Mini ($0.75 / $4.50).
There's no question Kimi models are very good for a lot of code tasks. They're the best quality open weight model. But to get similar overall outcomes as on Sonnet/Opus, on average you'll spend many more tokens and will have to do more managing of the model. You shouldn't look at price per token, you should look at how much you pay for the entire process.