[WhatsName]

If it were any good I would assume there would be no need to hype it up.

My theory is that LLMs will get commoditized within the next year. The edge that OpenAI had over the competition is arguably lost. If the trend continues we will be looking at inference like commodity prices, where the most efficient like cerebras and groq will be the only ones actually making money at the end.

[moojacob]

They already are. I have been using Kimi k2. It is 90% as good as Sonnet and on Groq 3x faster and 1/5th the price.

[pizzalife]

What kind of GPU setup are you using for Kimi?

[csomar]

That's an interesting name to choose. For second there, I thought GroK enabled third-party models.

[OldfieldFund]

isn't it Q4 quantized on groq?

[dimitri-vs]

I don't think so, look at how Sora changed every... Well Operator was a game changer for.. Hmm, but what about gpt-4.5 or PhD level o3... o3-pro...? I mean, the 10k/mon agents are definitely coming... any day now...

Anyway, I'm sure gpt-5 will be AGI.

[empath75]

> If it were any good I would assume there would be no need to hype it up.

Yes, this is why apple famously just dumped the original iphone on the market without telling anybody about it ahead of time.

[SiempreViernes]

With this comparison you are saying the original Iphone was like version 6 of an well established line of products in a market that had seen major releases a few times a year for about three years.

That's certainly not how the first iphone is usually described.

[Jackson__]

>If it were any good I would assume there would be no need to hype it up.

If it were good, there would also be no need for their devs to tell people to temper their expectations, alas... [0]

[0] https://xcancel.com/alexwei_/status/1946477756738629827#m

[j_timberlake]

"My theory is that LLMs will get commoditized within the next year."

Incredibly bad theory, it's like you're saying every LLM is the same because they can all talk, even though the newer ones continue to smash through benchmarks the older ones couldn't. And now it happens quarterly instead of yearly, so you can't even say it's slowing down.

[infecto]

At the moment most of the dollars are coming from consumer, inclusive of business, subscriptions. That’s where the valuations are getting pegged and most API dollars are probably seen as experimental. The model quality matters but product experience is what is driving revenue. In that sense OpenAI is doing quite well.

[janalsncm]

If that is the case, the $300 billion question is whether someone can create a product experience that is as good as OpenAI’s.

In my mind there are really three dimensions they can differentiate on: cost, speed, and quality. Cost is hard because they’re already losing money. Speed is hard because differentiation would require better hardware (more capex).

For many tasks, perhaps even a majority right now, quality of free models is approaching good enough.

OpenAI could create models which are unambiguously more reliable than the competition, or ones which are able to answer questions no other model can. Neither of those has happened yet afaik.

[tootie]

The fact that xAI only exists for Elon Musk's personal spite and they produced a top performing model certainly implies that model training isn't any kind of moat. It's certainly very expensive but not mysterious.

[ml-anon]

“Top performing model”

Ie overfit to benchmarks.

[jryle70]

Which year did Linux become the dominant desktop OS?