Over time, there might be an increasingly large gap between insider model access and outsider model access. By insiders, I mean employees at the frontier lab.[1] By "outsiders", I mean external safety researchers, third-party auditors, and other actors trying to make the future go well. I will call this a model access gap — and when the gap is small, I'll call this model access parity.[2]

I think that one of the top priorities for the external AI safety community over the next 6-12 months should be ensuring model access parity. Main reasons:

This would allow us to direct billions of dollars in AI labour towards making things go well. This seems robustly good, regardless of what activities we decide to actually direct the labour towards.
I think publicly available models will probably lag 3-6 months behind the best internal models. Hence, as R&D uplift grows superexponentially, we might see the differential uplift grow from 2x to 60x. In short: I think achieving model access parity might be preferable to scaling the headcount of outsider orgs by ten-fold.
Model access parity isn't too far from the status quo, but it's the kind of thing that we could lose [...]

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Outline:

(01:42) Which outsiders?

(02:24) Examples of outsiders

(04:12) Who aren't outsiders?

(05:26) What kinds of model access gap should we worry about?

(06:27) Non-release

(07:25) Deployment lag

(09:15) Safeguards

(10:43) Costs and rate limits

(12:06) Elicitation techniques (e.g. finetuning)

The original text contained 3 footnotes which were omitted from this narration.

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First published:
July 1st, 2026

Source:
https://www.lesswrong.com/posts/RuGZ5tMdqpnraJahJ/model-access-for-third-parties-it-s-a-big-deal

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Narrated by TYPE III AUDIO.

“Model access for third-parties — it’s a big deal!” by Cleo Nardo

LessWrong (30+ Karma)

“Model access for third-parties — it’s a big deal!” by Cleo Nardo