Regardless of the promise of the underlying technology, I do wonder about the long-term viability of companies like OpenAI and Anthropic. Not only are they quite beholden to companies like Nvidia or Google for hardware, but LLM tech as it stands right now will turn into a commodity.

It's why Amodei has spoken in favor of stricter export controls and Altman has pushed for regulation. They have no moat.

I'm thankful for the various open-weighted Chinese models out there. They've kept good pace with flagship models, and they're integral to avoiding a future where 1-2 companies own the future of knowledge labor. America's obsession with the shareholder in lieu of any other social consideration is ugly.

▲ chasd00 4 hours ago | parent | next [-]

I think google ends up the winner. They can keep chugging along and just wait for everyone else to go bankrupt. I guess apple sees it too since the signed with google and not OpenAI.

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stego-tech 3 hours ago | parent | next [-]

I’ll second this. Google’s investment in underlying accelerators is the big differentiator here, along with their existing datacenter footprint.

Everyone else has to build infrastructure. Google just had to build a single part, really, and already had the software footprint to shove it everywhere - and the advertising data to deliver features that folks actually wanted, but could also be monetized.

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martinald 2 hours ago | parent | next [-]

I was thinking about that (I definitely agree with you on the software and data angle).

But when you think about it it's actually a bit more complex. Right now (eg) OpenAI buys GPUs from (eg) NVidia, who buys HBM from Samsung and fabs the card on TSMC.

Google instead designs the chip, with I assume a significant amount of assistance of Broadcom - at least in terms of manufacturing, who then buys the HBM from the same supplier(s) and fabs the card with TSMC.

So I'm not entirely sure if the margin savings are that huge. I assume Broadcom charges a fair bit to manage the manufacturing process on behalf of Google. Almost certainly a lot less than NVidia would charge in terms of gross profit margins, but Google also has to pay for a lot of engineers to do the work that would be done in NVidia.

No doubt it is a saving overall - otherwise they wouldn't do it. But I wonder how dramatic it is.

Obviously Google has significant upside in the ability to customise their chips exactly how they want them, but NVidia (and to a lesser extent) AMD probably can source more customer workflows/issues from their broader set of clients.

I think "Google makes its own TPUs" makes a lot of people think that the entire operation in house, but in reality they're just doing more design work than the other players. There's still a lot of margin "leaking" through Broadcom, memory suppliers and TSMC so I wonder how dramatic it is really is

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coredog64 2 hours ago | parent | next [-]

My take is it's the inference efficiency. It's one thing to have a huge GPU cluster for training, but come inference time you don't need nearly so much. Having the TPU (and models purpose built for TPU) allows for best cost in serving at hyperscale.

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martinald 17 minutes ago | parent [-]

Yes potentially - but the OG TPUs were actually very poorly suited for LLM usage - designed for far smaller models with more parallelism in execution.

They've obviously adapted the design but it's a risk optimising in hardware like that - if there is another model architecture jump the risk of having a narrow specialised set of hardware means you can't generalise enough.

	▲	zozbot234 15 minutes ago \| parent [-]
		Prefill has a lot of parallelism, and so does decode with a larger context (very common with agentic tasks). People like to say "old inference chips are no good for LLM use" but that's not really true.

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flyinglizard 2 hours ago | parent | prev | next [-]

NVidia is operating with what, 70% gross margin? That’s what Google saves. Plus, Broadcom may be in for the design but I’m not sure they’re involved in the manufacturing of TPUs.

	▲	lizknope 2 hours ago \| parent [-]
		Broadcom does the physical design and sources a huge amount of the IP like serdes blocks. TSMC manufactures the chips.

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dyauspitr 2 hours ago | parent | prev [-]

What a wild situation to have a significant part of Earth’s major economies be directly reliant, not on one country, but on one building in the world.

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collingreen an hour ago | parent [-]

Yeah this is a bummer. If it goes south everyone in power will also have perfect hindsight and say they saw it coming because obviously you shouldn't have this much built on such a small footprint. And yet...

	▲	palmotea 30 minutes ago \| parent [-]
		> Yeah this is a bummer. If it goes south everyone in power will also have perfect hindsight and say they saw it coming because obviously you shouldn't have this much built on such a small footprint. And yet... It'll be true, everyone does see it coming (just like with rare earth minerals). But the market-infected Western society doesn't have the maturity to do anything about it. Businesses won't because they're expected to optimize for short-term financial returns, government won't because it's hobbled because biases against it (e.g. any failure becomes a political embarrassment, and there's a lot of pressure to stay out of areas where businesses operate and not interfere with businesses). America needs a lot more strategic government control of the economy, to kick businesses out of their short-term shareholder-focused thinking. If it can't manage that, it will decline into irrelevance.

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tummler an hour ago | parent | prev | next [-]

Google has the time, money, TPUs, and ability to siphon talent. It'll be an unsexy slog to the top, but they'll get there eventually.

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catlover76 an hour ago | parent | prev [-]

[dead]

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butlike 2 hours ago | parent | prev | next [-]

In addition to that, Google and Apple are demonstrated business partners. Google has consistently paid Apple billions to be the default search engine, so they have demonstrated they pay on time and are a known quantity. Imagine if OpenAI evaporated and Siri was left without a backend. It'd be too risky.

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Aboutplants 3 hours ago | parent | prev | next [-]

The minute Apple chose Google, OpenAI became a dead duck. It will float for a while but it cannot compete with the likes of Google, their unlimited pockets and better yet their access to data

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awongh 3 hours ago | parent | next [-]

I think it points to OpenAI trying to pivot to leveraging their brand awareness head start and optimizing for either ads or something like the Jony Ive device- focusing on the consumer side.

For now people identify LLMs and AI with the ChatGPT brand.

This seems like it might be the stickiest thing they can grab ahold of in the long term.

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cael450 3 hours ago | parent | next [-]

Consumer AI is not going to come close to bailing them out. They need B2B use cases. Anthropic is a little better positioned because they picked the most proven B2B use case — development — and focused hard on it. But they'll have to expand to additional use cases to keep up with their spend and valuation, which is why things like cowork exist.

But I tend to agree that the ultimate winner is going to be Google. Maybe Microsoft too.

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ghaff 2 hours ago | parent | next [-]

Consumers en masse aren't going to pay big $$s for AI. Maybe some specific embedded apps as part of other products.

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WarmWash an hour ago | parent [-]

They'll pay $60-$80/mo for it. Just watch.

Unless you're totally dumb or a super genius, LLMs can easily provide that kind of monthly value to you. This is already true for most SOTA models, and will only become more true as they get smarter and as society reconfigures for smoother AI integration.

Right now we are in the "get them hooked" phase of the business cycle. It's working really damn well, arguably better than any other technology ever. People will pay, they're not worried about that.

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zozbot234 an hour ago | parent | next [-]

It would have to be $60-$80/mo. in value over and above what you could get at the same time with cheap 3rd party inference on open models. That's not impossible depending on what kind of service they provide, but it's really hard.

	▲	ghaff 32 minutes ago \| parent \| next [-]
		I use LLMs now and then but not really regularly. I'm nowhere close to paying for a significant subscription today.
	▲	WarmWash an hour ago \| parent \| prev [-]
		The average cell phone bill in the US is $135/mo. Plans with unlimited talk/text and 5GB+ of data have been available for <$30 for over a decade now. The AI labs are not worried.

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gloryjulio an hour ago | parent | prev [-]

The value is well worth over $60-$80/mo. But conflating that with the market condition is very different.

In the world where you cheap open weight models and free tier closed sources models are flooding the market, you need very good reason to convince regular people to pay for just certain models en masse in b2c market

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WarmWash an hour ago | parent [-]

After 30 years with a shit operating system known as Windows, Linux still cannot get over 5% adoption. Despite being free and compatible with every computer.

"Regular People" know ChatGPT. They know Gemini (largely because google shoves it in their face). They don't know anything else (maybe Siri, because they don't know the difference, just that siri now sucks). I'm not sure if I would count <0.1% of tokens generated being "flooding the market".

Just like you don't give much thought to the breed of grass growing in your yard, they don't give much thought to the AI provider they are using. They pay, it does what they want, that's the end of it. These are general consumers, not chronically online tech nerds.

	▲	gloryjulio 35 minutes ago \| parent [-]
		> After 30 years with a shit operating system known as Windows, Linux still cannot get over 5% adoption. Despite being free and compatible with every computer. You need to install linux and actively debugging it. For ai, regular people can just easily switch around by opening an browser. There are many low or 0 barrir choices. Do you know windows 11 is mostly free too for b2c customers now? Nobody is paying for anything > "Regular People" know ChatGPT. They know Gemini (largely because google shoves it in their face). They don't know anything else (maybe Siri, because they don't know the difference, just that siri now sucks). I'm not sure if I would count <0.1% of tokens generated being "flooding the market". You just proved my point. Yes they are good, but why would people pay for it? Google earns money through ads mostly. > Just like you don't give much thought to the breed of grass growing in your yard, they don't give much thought to the AI provider they are using. They pay, it does what they want, that's the end of it. These are general consumers, not chronically online tech nerds. That's exactly the points, because most of the internet services are free. Nobody is paying for anything because they are ads supported

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surgical_fire 2 hours ago | parent | prev [-]

It doesn't matter. I firmly believe both OpenAI and Anthropic are toast. And I aay this as someone that uses both Codex and Claude primarily.

I really dislike Google, but it is painfully obvious they won this. Open AI and Anthropic bleed money. Google can bankroll Gemini indefinitely because they have a very lucrative ad business.

We can't even argue that bankrolling Gemini for them is a bad idea. With Gemini they can have yet another source of data to monetize users from. Technically Gemini can "cost" them money forever, and it would still pay for itself because with it they can know even more data about users to feed their ad business with. You tell LLMs things that they would never know otherwise.

Also, they mostly have the infrastructure already. While everyone spends tons of money to build datacenters, they have those already. Hell, they even make money by renting compute to AI competitor.

Barred some serious unprecedented regulatory action against them (very unlikely), I don't see how they would lose here.

Unfortunately, I might add. i consider Google an insidiously evil corporation. The world would be much better without it.

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ChoGGi 20 minutes ago | parent | prev | next [-]

> For now people identify LLMs and AI with the ChatGPT brand.

> This seems like it might be the stickiest thing they can grab ahold of in the long term.

For now, but do you still Xerox paper?

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raw_anon_1111 3 hours ago | parent | prev | next [-]

OpenAI is not going to fund themselves with $20 subscriptions and advertising enough to be profitable.

	▲	gruturo 2 hours ago \| parent [-]
		> OpenAI is not going to fund themselves with $20 subscriptions and advertising enough to be profitable. Then it's doomed. Which is also my opinion, I don't disagree at all with you.

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dakolli 3 hours ago | parent | prev [-]

Ads in GPT, might literally be the worst business decision ever made. Google can get away with Ads, its expected from them, but not OpenAI

	▲	_aavaa_ 3 hours ago \| parent \| next [-]
		Sergei and Brin were pretty vocal about the problems with ads and why they don't belong in search engines when they started. The only reason it's expected now is because of a slow boil.
	▲	duskdozer 3 hours ago \| parent \| prev [-]
		They ideally will not want you to realize you're looking at ads.

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xnx 14 minutes ago | parent | prev | next [-]

> OpenAI became a dead duck

Won't Microsoft own OpenAI after it flames out?

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johsole an hour ago | parent | prev [-]

I think Microsoft probably picks up all of OpenAI if OpenAI gets in financial trouble.

	▲	chasd00 12 minutes ago \| parent [-]
		Yes, I think that’s their plan. Remember when Altman got fired from OpenAI? Msoft was right there with open arms. Msoft is probably letting OpenAI do the dirty work of fleecing investors and then when all their money is gone doing the R/D, MSoft scoops up the IP and continues on.

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co_king_5 3 hours ago | parent | prev | next [-]

I hope I see Anthropic and OpenAI shutter within my lifetime.

Google has been guilty of all of the same crimes, but it bothers me to see new firms pop up with the same rapacious strategies. I hope Anthropic and OpenAI suffer.

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echelon 3 hours ago | parent [-]

You better hope Anthropic and OpenAI thrive, because a world in which Google is the sole winner is a nightmare.

Google's best trick was skirting the antitrust ruling against them by making the judge think they'd "lose" AI. What a joke.

Meanwhile they're camping everyone's trademarks, turning them into lucrative bidding wars because they own 92% of the browser URL bars.

Try googling for Claude or ChatGPT. Those companies are shelling out hundreds of millions to their biggest competitor to defend their trademarks. If they stop, suddenly they lose 60% of their traffic. Seems unfair, right?

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co_king_5 2 hours ago | parent | next [-]

I understand that Google is an extraordinarily bloated monopoly.

What I mean is that I am so bitter about OpenAI and Anthropic's social media manipulation and the effects of AI psychosis on the people around me that I would gladly accept a worse future and a less free society just to watch them suffer.

	▲	palmotea 16 minutes ago \| parent \| next [-]
		Also, Sam Altman (at least) gives the impression of being a bit of a manipulative psychopath. Even if there are others out there like him, who are just more competent at hiding their tendencies, I really don't want him to win the "world's richest man" jackpot; it'd be a bad lesson to others. Steve Jobs hero-worship is bad enough.
	▲	pfraze 2 hours ago \| parent \| prev [-]
		[flagged]

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PunchTornado 2 hours ago | parent | prev | next [-]

I'm waiting to see a more egregious company than openai and a bigger scammer ceo like altman. no, thank you. i hope openai goes bankrupt. especially since the ousting of ilya.

	▲	co_king_5 2 hours ago \| parent [-]
		> I'm waiting to see a more egregious company than openai and a bigger scammer ceo like altman. Anthropic and Dario Amodei are undoubtedly bigger scammers IMO.

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Imustaskforhelp 2 hours ago | parent | prev [-]

Honestly at this point, I don't care which company lives or dies.

Because recent open source models have reached my idea of "enough". I just want the bubble to burst, but I think the point of the bubble burst is that Anthropic and OpenAI couldn't survive whereas Google has chances of survival but even then we have open source models and the bubble has chances of reducing hardware costs.

OpenAI and Anthropic walked so that Google or Open source models could run but I wish competition and hope that maybe all these companies can survive but the token cost is gonna cost more, maybe that will tilt things more towards hardware.

I just want the bubble to burst because the chances of it prolonging would have a much severe impact than what improvements we might see in Open source models. And to be quite frank, we might be living an over-stimulus of "Intelligence", and has the world improved?

Everything I imagined in AI sort of reached and beyond and I am not satisfied with the result. Are you guys?

I mean, now I can make scripts to automate some things and some other things but I feel like we lost something so much more valuable in the process. I have made almost all of my projects with LLM's and yet they are still empty. Hollow.

So to me, the idea of bursting the bubble is of the utmost importance now because as long as the bubble continues, we are subsiziding the bubble itself and we are gonna be the one who are gonna face the most impact, and well already are facing it.

in hindsight, I think evolution has a part in this. We humans are so hard coded to not get outside of the tribe/the-newest-thing so maybe collectively us as a civiliazation can get dis-enchanted first via crypto now AI but we also can think for ourselves and the civilization is built from us in my naive view.

So the only thing we can do is think for ourselves and try to learn but it seems as if that's the very thing AI wants to offload.

Have a nice day.

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m-schuetz 3 hours ago | parent | prev | next [-]

Also Gemini works absolutely fantastic right now. I find it provides better results for coding tasks compared to ChatGPT

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frde 3 hours ago | parent | next [-]

Don't want to sound rude, but anytime anyone says this I assume they haven't tried using agentic coding tools and are still copy pasting coding questions into a web input box

I would be really curious to know what tools you've tried and are using where gemini feels better to use

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dudeinhawaii 11 minutes ago | parent | next [-]

My experience is that on large codebases that get tricky problems, you eventually get an answer quicker if you can send _all_ the context to a relevant large model to crunch on it for a long period of time.

Last night I was happily coding away with Codex after writing off Gemini CLI yet again due to weirdness in the CLI tooling.

I ran into a very tedious problem that all of the agents failed to diagnose and were confidently patching random things as solutions back and forth (Claude Code - Opus 4.6, GPT-5.3 Codex, Gemini 3 Pro CLI).

I took a step back, used python script to extract all of the relevant codebase, and popped open the browser and had Gemini-3-Pro set to Pro (highest) reasoning, and GPT-5.2 Pro crunch on it.

They took a good while thinking.

But, they narrowed the problem down to a complex interaction between texture origins, polygon rotations, and a mirroring implementation that was causing issues for one single "player model" running through a scene and not every other model in the scene. You'd think the "spot the difference" would make the problem easier. It did not.

I then took Gemini's proposal and passed it to GPT-5.3-Codex to implement. It actually pushed back and said "I want to do some research because I think there's a better code solution to this". Wait a bit. It solved the problem in the most elegant and compatible way possible.

So, that's a long winded way to say that there _is_ a use for a very smart model that only works in the browser or via API tooling, so long as it has a large context and can think for ages.

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f311a 3 hours ago | parent | prev | next [-]

It's good enough if you don't go wild and allow LLMs to produce 5k+ lines in one session.

In a lot of industries, you can't afford this anyway, since all code has to be carefully reviewed. A lot of models are great when you do isolated changes with 100-1000 lines.

Sometimes it's okay to ship a lot of code from LLMs, especially for the frontend. But, there are a lot of companies and tasks where backend bugs cost a lot, either in big customers or direct money. No model will allow you to go wild in this case.

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parliament32 44 minutes ago | parent | prev | next [-]

Every time I've tried to use agentic coding tools it's failed so hard I'm convinced the entire concept is a bamboozle to get customers to spend more tokens.

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gman83 3 hours ago | parent | prev | next [-]

You need to stick Gemini in a straightjacket; I've been using https://github.com/ClavixDev/Clavix. When using something like that, even something like Gemini 3 Flash becomes usable. If not, it more often than not just loses the plot.

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segfaultex 3 hours ago | parent | prev | next [-]

Conversely, I have yet to see agentic coding tools produce anything I’d be willing to ship.

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m00x 3 hours ago | parent | prev [-]

Gemini is a generalist model and works better than all existing models at generalist problems.

Coding has been vastly improved in 3.0 and 3.1, but Google won't give us the full juice as Google usually does.

	▲	FartyMcFarter 3 hours ago \| parent [-]
		My guess is that Google has teams working on catching up with Claude Code, and I wouldn't be surprised if they manage to close the gap significantly or even surpass it. Google has the datasets, the expertise, and the motivation.

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kdheiwns 3 hours ago | parent | prev | next [-]

I've had the same experience with editing shaders. ChatGPT has absolutely no clue what's going on and it seems like it randomly edits shader code. It's never given me anything remotely usable. Gemini has been able to edit shaders and get me a result that's not perfect, but fairly close to what I want.

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logicallee 3 hours ago | parent | prev | next [-]

have you compared it with Claude Code at all? Is there a similar subscription model for Gemini as Claude? Does it have an agent like Claude Code or ChatGPT Codex? what are you using it for? How does it do with large contexts? (Claude AI Code has a 1 million token context).

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landl0rd 3 hours ago | parent | next [-]

- yes, pretty close to opus performance

- yes

- yes (not quite as good as CC/Codex but you can swap the API instead of using gemini-cli)

- same stuff as them

- better than others, google got long (1mm) context right before anyone else and doesn't charge two kidneys, an arm, and a leg like anthropic

	▲	logicallee 2 hours ago \| parent [-]
		thanks for these answers.

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airstrike 3 hours ago | parent | prev [-]

it's nowhere near claude opus

but claude and claude code are different things

	▲	dudeinhawaii a minute ago \| parent \| next [-]
		My take has been... Gemini 3.1 (and Gemini 3) are a lot smarter than Claude Opus 4.6 But... Gemini 3 series are both mediocre at best in agentic coding. Single shot question(s) about a code problem vs "build this feature autonomously". Gemini's CLI harness is just not very good and Gemini's approach to agentic coding leaves a lot to be desired. It doesn't perform the double-checking that Codex does, it's slower than Claude, it runs off and does things without asking and not clearly explaining why.
	▲	logicallee 2 hours ago \| parent \| prev [-]
		(Claude Code now runs claude opus, so they're not so different.) >it's [Gemini] nowhere near claude opus Could you be a bit more specific, because your sibling reply says "pretty close to opus performance" so it would help if you gave additional information about how you use it and how you feel the two compare. Thanks.

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nobody_r_knows 3 hours ago | parent | prev [-]

ChatGTP isn't even meant for coding anymore, nor Gemini. It's OpenAI Codex vs Claude Code. Gemini doesn't even have an offering.

	▲	input_sh 3 hours ago \| parent \| next [-]
		https://antigravity.google/ On top of every version of Gemini, you also get both Claude models and GPT-OSS 120B. If you're doing webdev, it'll even launch a (self-contained) Chrome to "see" the result of its changes. I haven't played around Codex, but it blows Claude Code's finicky terminal interface out of the water in my experience.
	▲	pastjean 3 hours ago \| parent \| prev \| next [-]
		opencode + gemini is pretty nicely working
	▲	3 hours ago \| parent \| prev [-]
		[deleted]

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xnx 22 minutes ago | parent | prev | next [-]

In a few years this will amazingly alway have been obvious to everyone.

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hansmayer 3 hours ago | parent | prev | next [-]

It is a rather attractive view, and I used to hold it too. However, seeing as Alphabet recently issued 100-year bonds to finance the AI CapEx bloat, means they are not that far off from the rest of the AI "YOLO"s currently jumping off the cliff ...

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jazzypants 2 hours ago | parent | next [-]

They have over $100B in cash on hand. I can't pretend to understand their financial dealings, but they have a lot more runway before that cliff than most of the other companies.

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gorgolo 2 hours ago | parent | prev [-]

If someone is willing to fund you with a 100y bond, and it gives you extra cash to move even a bit faster, it sounds like a pretty good deal.

One thing I don’t get though, if superintelligence is really 5 years away, what’s going to be the point of a fixed-interest 100y bond.

	▲	hansmayer an hour ago \| parent [-]
		Motorola was I think the last company to issue a 100-year bond in the 90s. Whatever happened to Motorola?

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sethops1 3 hours ago | parent | prev | next [-]

This is the conclusion I came to as well. Either make your own hardware, or drown paying premiums until you run out of money. For a while I was hopeful for some competition from AMD but that never panned out.

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duped 11 minutes ago | parent | prev | next [-]

Google has proven themselves to be incapable of monetizing anything besides ads. One should be deeply skeptical of their ability to bring consumer software to market, and keep it there.

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alex1138 34 minutes ago | parent | prev | next [-]

Now if only Google could a) drop its commitment to censorship and b) stop prioritizing Youtube links in its answers

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piker 4 hours ago | parent | prev | next [-]

And what about Microsoft?

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mrbungie 4 hours ago | parent | next [-]

They don't have the know how (except by proxy via OpenAI) nor custom hardware and somehow they are even worse at integrating AI into their products than Google.

	▲	raw_anon_1111 3 hours ago \| parent [-]
		They don’t need to. Just like Amazon they are seeing record revenues from Azure because of their third party LLM hosting platforms only being gated because no one can get enough chips right now

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napolux 4 hours ago | parent | prev [-]

See Apple in my previous comment

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napolux 4 hours ago | parent | prev | next [-]

downvote all you want. google has all the money to keep up and just wait for the others to die. apple is a different story, btw, can probably buy openai or anthropic, but for now they're just waiting like google, and since they need to provide users AI after the failure with Apple Intelligence, they prefer to pay for Google and wait for the others to fight against each other.

openai and anthropic know already what will happen if they go public :)

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r0b05 3 hours ago | parent | next [-]

What will happen if they go public?

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mrcwinn 3 hours ago | parent | prev | next [-]

That’s not a well informed argument. Even if Apple could finance the $1T+ it would cost to buy Anthropic - they’re not making that money back by making the iPhone a little better. The only way to monetize is by selling, as Anthropic does, enterprise services to businesses. And that’s not Apple’s “DNA,” to use their language.

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aurizon 3 hours ago | parent | prev [-]

Google is vulnerable in search and that already shows as we see a decline as many parallel paths emerge. At the beginning it was a simple lookup for valid information and it became dominant - then pages of pay ranked preference spots filled pages that obscured what you wanted = it became evil.

	▲	raw_anon_1111 3 hours ago \| parent \| next [-]
		We see no such thing. Google just announces review revenue and profit and Apple hinted at it not seeing any decline in revenue from their search deal with Google which is performance based.
	▲	wooger 3 hours ago \| parent \| prev [-]
		And Gemini is already integrated into the results page and gives useful answers instantly, alongside advertising... What problem for google are you seeing?

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neya 3 hours ago | parent | prev [-]

Google is the new Open AI. Open AI is the new Google. Guess who wants to shove advertisements into paying customers' face and take a % of their revenues for using their models to build products? Not Google.

	▲	pell 3 hours ago \| parent \| next [-]
		>Not Google. Google's main revenue source (~ 75%) is advertising. They will absolutely try to shove in ads into their AI offerings. They simply don't have to do it this quickly.
	▲	ipaddr 3 hours ago \| parent \| prev \| next [-]
		The majority of people who use Google for AI encounter it at the top of an ad filled search engine.
	▲	SecretDreams 3 hours ago \| parent \| prev \| next [-]
		> Guess who wants to shove advertisements into paying customers' face and take a % of their revenues for using their models to build products? Not Google. But, also, probably google.
	▲	Forgeties79 3 hours ago \| parent \| prev [-]
		Don’t worry, Google is profiting off of your data one way or another lol

▲ munk-a 18 minutes ago | parent | prev | next [-]

OpenAI is not viable. OpenAI is spending like Google without a warchest and they have essentially nothing to offer outside of brand recognition. Nvidia propping them up to force AI training to be done on their chips vs. google in-house cores is their only viable path forward. Even if they develop a strong model the commitments they've made are astronomically out of reach of all but the largest companies and AI has proven to be a very low moat market. They can't demand a markup sufficient to justify that spend - it's too trivial to undercut them.

Google/Apple/Nvidia - those with warchests that can treat this expenditure as R&D, write it off, and not be up to their eyeballs in debt - those are the most likely to win. It may still be a dark-horse previously unknown company but if it is that company will need to be a lot more disciplined about expenditures.

▲ 34679 2 hours ago | parent | prev | next [-]

I can't shake the feeling that the RAM shortage was intentionally created to serve as a sort of artificial moat by slowing or outright preventing the adoption of open weight models. Altman is playing with hundreds of billions of other people's dollars, trying to protect (in his mind) a multi-trillion dollar company. If he could spend a few billion to shut down access to the hardware people need to run competitor's products, why wouldn't he?

	▲	zozbot234 an hour ago \| parent \| next [-]
		It's very difficult to "intentionally create" a real shortage. You can hoard as much as you want, but people will expect you to dump it all right back onto the market unless you really have a genuine higher-value use for the stuff you hoarded (And then you didn't intentionally create anything, you just bought something you needed!). Plus producers will now feel free to expand production and dump even more onto the market. This is great if you needed that amount of supply, but it's terrible if you were just trying to deprive others.
	▲	tmaly an hour ago \| parent \| prev [-]
		Hard drives and GPUs seem to be facing the same fate.

▲ sigmar 2 hours ago | parent | prev | next [-]

>various open-weighted Chinese models out there. They've kept good pace with flagship models,

I don't think this is accurate. Maybe it will change in the future but it seems like the Chinese models aren't keeping up with actually training techniques, they're largely using distillation techniques. Which means they'll always be catching up and never at the cutting edge. https://x.com/Altimor/status/2024166557107311057

▲ parliament32 41 minutes ago | parent | next [-]

Does that actually matter? If "catching up" means "a few months behind" at worst for.. free?

	▲	sigmar 21 minutes ago \| parent [-]
		For certain use-cases, sure it doesn't matter. but that doesn't make those models cutting edge. Some use-cases are adversarial, and 1% lower efficacy matters a lot.

▲ A_D_E_P_T 2 hours ago | parent | prev | next [-]

> they're largely using distillation techniques. Which means they'll always be catching up and never at the cutting edge.

You link to an assumption, and one that's seemingly highly motivated.

Have you used the Chinese models? IMO Kimi K2.5 beats everything but Opus 4.6 and Gemini 3.1... and it's not exactly inferior to the latter, it's just different. It's much better at most writing tasks, and its "Deep Research" mode is by a wide margin the best in the business. (OpenAI's has really gone downhill for some reason.)

	▲	nwlieb 2 hours ago \| parent [-]
		Have you tried the OpenAI deep research in the past week or so? It's been updated to use 5.2 https://x.com/OpenAI/status/2021299935678026168 (I work at OpenAI, but on the infra side of things not on models)

▲ arthurcolle 2 hours ago | parent | prev [-]

I have been using a quorum composed of step-3.5-flash, Kimi k2.5 and glm-5 and I have found it outperforms opus-4.5 at a fraction of the cost

That's pretty cutting edge to me.

EDIT: It's not a swarm — it's closer to a voting system. All three models get the same prompt simultaneously via parallel API calls (OpenAI-compatible endpoints), and the system uses weighted consensus to pick a winner. Each model has a weight (e.g. step-3.5-flash=4, kimi-k2.5=3, glm-5=2) based on empirically observed reliability.

The flow looks like:

  1. User query comes in
  2. All 3 models (+ optionally a local model like qwen3-abliterated:8b) get called in parallel
  3. Responses come back in ~2-5s typically
  4. The system filters out refusals and empty responses
  5. Weighted voting picks the winner — if models agree on tool use (e.g. "fetch this URL"), that action executes
  6. For text responses, it can also synthesize across multiple candidates

The key insight is that cheap models in consensus are more reliable than a single expensive model. Any one of these models alone hallucinates or refuses more than the quorum does collectively. The refusal filtering is especially useful — if one model over-refuses, the others compensate.

Tooling: it's a single Python agent (~5200 lines) with protocol-based tool dispatch — 110+ operations covering filesystem, git, web fetching, code analysis, media processing, a RAG knowledge base, etc. The quorum sits in front of the LLM decision layer, so the agent autonomously picks tools and chains actions. Purpose is general — coding, research, data analysis, whatever. I won't include it for length but I just kicked off a prompt to get some info on the recent Trump tariff Supreme Court decision: it fetched stock data from Benzinga/Google Finance, then researched the SCOTUS tariff ruling across AP, CNN, Politico, The Hill, and CNBC, all orchestrated by the quorum picking which URLs to fetch and synthesizing the results, continuing until something like 45 URLs were fully processed. Output was longer than a typical single chatbot response, because you get all the non-determinism from what the models actually ended up doing in the long-running execution, and then it needs to get consensus, which means all of the responses get at least one or N additional passes across the other models to get to that consensus.

  Cost-wise, these three models are all either free-tier or pennies per million tokens. The entire session above (dozens of quorum rounds, multiple web fetches) cost less than a single Opus prompt.

	▲	earth2mars 2 hours ago \| parent \| next [-]
		When you say quorum what do you mean? Is it like an agent swarm or using all of them in your workflow and independently they perform better than opus? Curious how you use (tooling and purpose - coding?)
	▲	tmaly an hour ago \| parent \| prev [-]
		I have not heard of step-3.5-flash before. But as the other commenter asked, I would love to hear about your quorum technique. What type of projects are you building with the quorum?

▲ enceladus06 3 hours ago | parent | prev | next [-]

OpenAI and Anthropic don't have a moat. We will have actual open models like DeepSeek and Kimi with the same functionality as Opus 4.6 in Claude Code <6mo IMO. Competition is a good thing for the end-user.

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zozbot234 3 hours ago | parent | next [-]

The open-weight models are great but they're roughly a full year behind frontier models. That's a lot. There's also a whole lot of uses where running a generic Chinese-made model may be less than advisable, and OpenAI/Anthropic have know-how for creating custom models where appropriate. That can be quite valuable.

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coder543 2 hours ago | parent | next [-]

I would not say a full year... not even close to a year: GLM-5 is very close to the frontier: https://artificialanalysis.ai/

Artificial Analysis isn't perfect, but it is an independent third party that actually runs the benchmarks themselves, and they use a wide range of benchmarks. It is a better automated litmus test than any other that I've been able to find in years of watching the development of LLMs.

And the gap has been rapidly shrinking: https://www.youtube.com/watch?v=0NBILspM4c4&t=642s

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zozbot234 2 hours ago | parent [-]

Benchmarks are always fishy, you need to look at things that you'd use the model for in the real world. From that point of view, the SOTA for open models is quite behind.

	▲	lancebeet 34 minutes ago \| parent \| next [-]
		If benchmarks are fishy, it seems their bias would be to produce better scores than expected for proprietary models, since they have more incentives to game the benchmarks.
	▲	coder543 2 hours ago \| parent \| prev [-]
		No... benchmarks are not always "fishy." That is just a defense people use when they have nothing else to point to. I already said the benchmarks aren't perfect, but they are much better than claiming vibes are a more objective way to look at things. Yes, you should test for your individual use case, which is a benchmark. As I said, I have been following this stuff closely for many years now. My opinion is not informed just by looking at a single chart, but by a lot of experience. The chart is less fishy than blanket statements about the closed models somehow being way better than the benchmarks show.

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mattmaroon 3 hours ago | parent | prev [-]

That's a lot now, in the same way that a PC in 1999 vs a PC in 2000 was a fairly sizeable discrepancy. At some point, probably soon, progress will slow, and it won't be much.

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jnovek 3 hours ago | parent | prev [-]

I just did a test project using K2.5 on opencode and, for me, it doesn’t even come close to Claude Code. I was constantly having to wrangle the model to prevent it from spewing out 1000 lines at once and it couldn’t hold the architecture in its head so it would start doing things in inconsistent ways in different parts of the project. What it created would be a real maintenance nightmare.

It’s much better than the previous open models but it’s not yet close.

▲ ahussain an hour ago | parent | prev | next [-]

People were saying the same last year, and then Anthropic launched Claude Code which is already at a $2.5B revenue run rate.

LLMs are useful and these companies will continue to find ways to capture some of the value they are creating.

▲ AznHisoka 3 hours ago | parent | prev | next [-]

Anthropic at least seems to be doing well with enterprises. OpenAI doesnt have that level of trust with enterprise use cases, and commodization is a bigger issue with consumers, when they can just switch to another tool easily

▲ idopmstuff 2 hours ago | parent | prev | next [-]

I do think the models themselves will get commoditized, but I've come around to the opinion that there's still plenty of moat to be had.

On the user side, memory and context, especially as continual learning is developed, is pretty valuable. I use Claude Code to help run a lot of parts of my business, and it has so much context about what I do and the different products I sell that it would be annoying to switch at this point. I just used it to help me close my books for the year, and the fact that it was looking at my QuickBooks transactions with an understanding of my business definitely saved me a lot of time explaining.

On the enterprise side, I think businesses are going to be hesitant to swap models in and out, especially when they're used for core product functionality. It's annoying to change deterministic software, and switching probabilistic models seems much more fraught.

▲ wejwej 3 hours ago | parent | prev | next [-]

To take the other side of this, as computers got commodified there still was a massive benefit to using cloud computing. Could it be possible that that happens with LLMs as well as hardware becomes more and more specialized? I personally have no idea but love that there’s a bunch of competition and totally agree with your point regulation and export controls are just ways to make it harder for new orgs to compete.

▲ ulfbert_inc 3 hours ago | parent | prev | next [-]

>LLM tech as it stands right now will turn into a commodity

I am yet to see in-depth analysis that supports this claim

	▲	otabdeveloper4 2 hours ago \| parent [-]
		It's already a commodity. The strongest use case is self-hosted pornography generation.

▲ tinyhouse an hour ago | parent | prev | next [-]

Openai is just playing catchup at this point, they completely lost thier way in my view.

Anthropic on the other hand is very capable and given the success of claude code and cowork, I think they will maintain their lead across knowledge work for a long time just by having the best data to keep improving their models and everything around. It's also the hottest tech conpany rn, like Google were back in the day.

If I need to bet on two companies that will win the AI race in the west, it's Anthropic and Google. Google on the consumer side mostly and Anthropic in enterprise. OpenAI will probably IPO soon to shift the risk to the public.

▲ jpalomaki 3 hours ago | parent | prev | next [-]

Both Anthropic and OpenAI are working hard to move away from being "just" the LLM provider on the background.

▲ KoolKat23 3 hours ago | parent | prev | next [-]

Anthropic I feel will be alright. They have their niche, it's good and people actually do pay for their services. Why do people still use salesforce when there's other free CRM's. They also haven't from what I can tell scaled for some imaginary future growth.

OpenAI I'm sorry to say are all over the place. They're good at what they do, but they try to do too much and need near ponzi style growth to sustain their business model.

▲ delaminator 4 hours ago | parent | prev | next [-]

Anthropic is also using lots of Amazon hardware for inference.

▲ nvarsj 3 hours ago | parent | prev | next [-]

I don't think you can put OpenAI and Anthropic together like that.

Anthropic has actually cracked Agentic AI that is generally useful. No other company has done that.

▲ llm_nerd 3 hours ago | parent | prev | next [-]

Anthropic, at least, has gone to lengths to avoid hardware lock-in or being open to extortion of the nvidia variety. Anthropic is running their models on nvidia GPUs, but also Amazon Trainium and Google's TPUs. Massive scale-outs on all three, so clearly they've abstracted their operations enough that they aren't wed to CUDA or anything nvidia-specific.

Similarly, OpenAI has made some massive investments in AMD hardware, and have also ensured that they aren't tied to nvidia.

I think it's nvidia that has less of a moat than many imagine they do, given that they're a $4.5T company. While small software shops might define their entire solution via CUDA, to the large firms this is just one possible abstraction engine. So if an upstart just copy pastes a massive number of relatively simple tensor cores and earns their business, they can embrace it.

▲ deepriverfish 2 hours ago | parent | prev | next [-]

they might end up like Dropbox

▲ techpression 4 hours ago | parent | prev | next [-]

How is censorship / ”alternative information” affecting them? Genuinely curious as I’ve only read briefly about it and it was ages ago.

	▲	whynotmaybe 3 hours ago \| parent [-]
		I've tried deepseek a few months ago and asket about the Tiananmen square protests and massacre. At first the answer was "I can't say anything that might hurt people" but with a little persuasion it went further. The answer wasn't the current official answer but way more nuanced that Wikipedia's article. More in the vein of "we don't know for sure", "different versions", "external propaganda", "some officials have lied and been arrested since" In the end, when I asked whether I should trust the government or ask for multiple source, it strongly suggested to use multiple sources to form an opinion. = not as censored as I expected.

▲ lvl155 3 hours ago | parent | prev | next [-]

Think LLM by itself is basically a commodity at this point. Not quite interchangeable but it’s more of artistic differences rather than technological. I used to think it was data and that would give companies like Google a leg up.

▲ 999900000999 2 hours ago | parent | prev [-]

They'll ban Chinese models, or do something like calling them security risks without proof.

Enterprise customers will gladly pay 10x to 20x for American models. Of course this means American tech companies will start to fall behind, combined with our recent Xenophobia.

Almost all the top AI researchers are either Chinese nationals or recent immigrants. With the way we've been treating immigrants lately ( plenty of people with status have been detained, often for weeks), I can't imagine the world's best talent continuing to come here.

It's going to be an interesting decade y'all.