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Open models by OpenAI

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Re: Open models by OpenAI

#311

Open models are going to win long-term. Anthropics' own research has to use OSS models [0]. China is demonstrating how quickly companies can iterate on open models, allowing smaller teams access and augmentation to the abilities of a model without paying the training cost. My personal prediction is that the US foundational model makers will OSS something close to N-1 for the next 1-3 iterations. The CAPEX for the fou…

> Open models are going to win long-term.

[3 of 3] What would it take for this statement to be false or missing the point?

Maybe we find ourselves in a future where:

- Yes, open models are widely used as base models, but they are also highly customized in various ways (perhaps by industry, person, attitude, or something else). In other words, this would be a blend of open and closed.

- Maybe publishing open weights of a model is more-or-less irrelevant, because it is "table stakes" ... because all the key differentiating advantages have to do with other factors, such as infrastructure, non-LLM computational aspects, regulatory environment, affordable energy, customer base, customer trust, and probably more.

- The future might involve thousands or millions of highly tailored models

Re: Open models by OpenAI

#312

I'm out of the loop for local models. For my M3 24gb ram macbook, what token throughput can I expect? Edit: I tried it out, I have no idea in terms of of tokens but it was fluid enough for me. A bit slower than using o3 in the browser but definitely tolerable. I think I will set it up in my GF's machine so she can stop paying for the full subscription (she's a non-tech professional)

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Re: Open models by OpenAI

#315

What a day! Models aside, the Harmony Response Format[1] also seems pretty interesting and I wonder how much of an impact it might have in performance of these models. [1] https://github.com/openai/harmony

Seems to be breaking every agentic tool I've tried so far.

Im guessing it's going to very rapidly be patched into the various tools.

Re: Open models by OpenAI

#316
The 120B model badly hallucinates facts on the level of a 0.6B model.

My go to test for checking hallucinations is 'Tell me about Mercantour park' (a national park in south eastern France).

Easily half of the facts are invented. Non-existing mountain summits, brown bears (no, there are none), villages that are elsewhere, wrong advice ('dogs allowed' - no they are not).

Re: Open models by OpenAI

#317

Open models are going to win long-term. Anthropics' own research has to use OSS models [0]. China is demonstrating how quickly companies can iterate on open models, allowing smaller teams access and augmentation to the abilities of a model without paying the training cost. My personal prediction is that the US foundational model makers will OSS something close to N-1 for the next 1-3 iterations. The CAPEX for the fou…

> Once someone hits AGI/SGI

I don't think there will be such a unique event. There is no clear boundary. This is a continuous process. Modells get slightly better than before.

Also, another dimension is the inference cost to run those models. It has to be cheap enough to really take advantage of it.

Also, I wonder, what would be a good target to make profit, to develop new things? There is Isomorphic Labs, which seems like a good target. This company already exists now, and people are working on it. What else?

Re: Open models by OpenAI

#318

So this confirms a best-in-class model release within the next few days? From a strategic perspective, I can't think of any reason they'd release this unless they were about to announce something which totally eclipses it?

GPT-5 coming Thursday.

Is this the stealth models horizon alpha and beta? I was generally impressed with them(although I really only used it in chats rather than any code tasks). In terms of chat I increasingly see very little difference between the current SOTA closed models and their open weight counterparts.

Re: Open models by OpenAI

#320
post #135

Earlier quoted context omitted.

here's a quick recording from the 20b model on my 128GB M4 Max MBP: https://asciinema.org/a/AiLDq7qPvgdAR1JuQhvZScMNr and the 120b: https://asciinema.org/a/B0q8tBl7IcgUorZsphQbbZsMM I am, um, floored

Generation is usually fast, but prompt processing is the main limitation with local agents. I also have a 128 GB M4 Max. How is the prompt processing on long prompts? processing the system prompt for Goose always takes quite a while for me. I haven't been able to download the 120B yet, but I'm looking to switch to either that or the GLM-4.5-Air for my main driver.

You mentioned "on local agents". I've noticed this too. How do ChatGPT and the others get around this, and provide instant responses on long conversations?
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