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by root_axis4 hours ago |
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upvoteby repeekad4 hours ago|
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Meta is selling their now excess compute, other compute has been on the market for a while. The current hardware cost bubble is temporary, especially once people are forced to pay the real inference price instead of majorly subsidized subscriptions.
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upvoteby program_whiz3 hours ago|
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yep, all those coders paying $200-$500 per day to use claude once subsidy ends will be seriously rethinking how much they really want to vibe-code "rewriting X in rust". Helping people write word docs, recipes, and emails isn't going to justify $15K per month subscriptions either.
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upvoteby apitman3 hours ago|
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> Helping people write word docs, recipes, and emails isn't going to justify $15K per month subscriptions either.

Those things can all be done today on a $250 used video card and pennies of electricity

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upvoteby km3r1 hours ago|
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The subscription is certainly subsidized but its no where near 100x cheaper than API prices.

Heck, most large enterprise moved to usage based billing and are still happily paying for it. They are force multipliers for your top talent, and when a top engineer is being paid $500k a year, doubling their output for $500/day is a no brainer.

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upvoteby bigyabai4 hours ago|
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Lowering the cost of hardware still won't solve the issue. HBM and DDR5 was never cheap, even before the shortages, so selling a full inference system is beyond the acceptable price range for most casual customers.

We're going to see Apple and Google compete over services and AI/OS integration instead, it will probably be years before your OEM takes local models seriously.

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upvoteby tanseydavid3 hours ago|
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Apple and Google (via smartphones) are in literally everyone's pocket.

Running KIMI on a phone is not possible today and I agree with you that it will "probably be years before..." it is.

But how many years do you guess? I personally do not think it will take even 10 years for the situation to be commonplace.

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upvoteby bigyabai13 minutes ago|
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> I personally do not think it will take even 10 years for the situation to be commonplace.

Do you personally remember how far smartphones progressed in the past 10 years? It's not as long a time as you think it is, the limits of what a smartphone GPU is capable of did not substantially change in that time. Nor did the amount of onboard RAM that we include in the package. This is true even for Nvidia's ARM SOCs, frankly.

Apple, Microsoft and Google all eventually want to enforce OS-level lock-in for the most profitable AI services (eg. their own). It's much more attainable and profitable to use that lock-in to sell you exclusive service integration, the local AI revolution probably won't begin on their hardware.

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upvoteby mark_l_watson54 minutes ago|
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You may be correct but the combination of local models when they are fast enough and work, combined with paying close to zero for deepseek v4 flash from US providers is pretty good. When you need it, glm5.2 is cheap to use and very good for working with larger projects.
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upvoteby switchbak4 hours ago|
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For the near future it seems that the new models will consume whatever improved hardware capacity we have. Competing with that is challenging, but I also think there will be strong economic incentives towards cheaper but adequate models on other providers.

I don't think we'll see home users being able to match even the low end clouds for a long time.

Longer term I think we'll see these uses of AI cluster into a few groups:

- maximal code / reasoning quality, at high prices (Fable)

- typical code / agents (sub-Opus, Terra)

- cheap but decent enough quality (think Deepseek / GLM / Luna)

- so cheap I don't care about utilization (Deepseek, and friends)

And also more niche ones:

- ultra fast with high quality answers (typically sub-SOTA). Cerebras / dedicated silicon type approaches, expensive.

- ultra fast with mostly-adequate answers, and an openness to retries, moving up to better models

I think the open models will dominate (not with individuals, but low cost providers) all except the top 1-2 of those categories, and there will be a continuous erosion on the big player's moats. The top categories are also where all the money is, but I'm not sure it can justify those investments long-term. I also think they will have to squeeze more money out of them to justify the investments, which will also drive people down the list.

Edit: clarifications.

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upvoteby asadotzler1 hours ago|
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>For the near future it seems that the new models will consume whatever improved hardware capacity we have.

But they're not. Meta, SpaceX, Microsoft, Amazon, they're all leasing out capacity to others. If they were truly constrained, we wouldn't see that happening.

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upvoteby honeycrispy4 hours ago|
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There will be plenty of model providers with prices that undercut Anthropic/OpenAI's prices.
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upvoteby root_axis4 hours ago|
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Doubtful for the same reasons. The frontier providers are working at a hardware scale that will make it impractical to undercut them.

I wouldn't rule out the possibility completely, but it won't be very common.

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upvoteby honeycrispy2 hours ago|
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They also have to pay for staff / model training. Those are not cheap.
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