Based on their own published benchmarks, it appears that this model is at least 6 months behind.

Strange how things evolve. When ChatGPT started it had about 2 years headstart over Google's best proprietary model, and more than 2 years ahead to open source models.

Now they have to be lucky to be 6 months ahead to an open model with at most half the parameter count, trained on 1%-2% the hardware US models are trained on.

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rglullis 5 hours ago | parent | next [-]

And more than that, the need for people/business to pay the premium for SOTA getting smaller and smaller.

I thought that OpenAI was doomed the moment that Zuckerberg showed he was serious about commoditizing LLM. Even if llama wasn't the GPT killer, it showed that there was no secret formula and that OpenAI had no moat.

	▲	NitpickLawyer 5 hours ago \| parent [-]
		> that OpenAI had no moat. Eh. It's at least debatable. There is a moat in compute (this was openly stated at a meeting of AI tech ceos in china, recently). And a bit of a moat in architecture and know-how (oAI gpt-oss is still best in class, and if rumours are to be believed, it was mostly trained on synthetic data, a la phi4 but with better data). And there are still moats around data (see gemini family, especially gemini3). But if you can conjure up compute, data and basic arch, you get xAI which is up there with the other 3 labs in SotA-like performance. So I'd say there are some moats, but they aren't as safe as they'd thought they'd be in 2023, for sure.

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rbtprograms 5 hours ago | parent | prev [-]

it seems they believed that superior models would be the moat, but when deepseek essentially replicated o1 they switched to the ecosystem as the moat.