If the belief that open-weight/Chinese models depend significantly on distillation of the latest frontier models is correct, then presumably the gap will stabilise to the minimum time required for extraction of meaningful data (from the latest frontier model) plus finalisation of training of the latest dependent model. This gap can be minimised by increasing the process efficiency, but can't be eliminated entirely. (Attempts to hinder distillation from Anthropic/OpenAI may shift the balance too.)
The gap between open weights LLMs and closed source LLMs
171–180 of 264 posts
Re: The gap between open weights LLMs and closed source LLMs
#172At this point, I think open weights vs proprietary models is a misnomer.
First, we can not be sure the next release will remain open weights as Qwen 3.7 has showed.
And second, they are all Chinese models. So instead of open weights, perhaps Chinese AI models is a better word choice.
Re: The gap between open weights LLMs and closed source LLMs
#173Earlier quoted context omitted.
The model itself, sure; the comment is about the production of more advanced models (to keep open weights near the frontier).
The proprietary spigots can be turned off at any time also. To me, that seems more likely.
I'd call 'more likely' an extremely safe take given that it's exactly what's happening right now
Re: The gap between open weights LLMs and closed source LLMs
#174IMHO, the biggest problem with the future of open weights models is that currently, open weights models are the result of philanthropy by some private org. (e.g. DeepSeek). The spigot can be turned off at any time. Until there's some sort of "community owned hardware", open weights models are always at risk of being discontinued.
I am the original author of the post - thanks for reading it!
I think the future of open weights models will be similar to fabless chip design companies. There will be companies that can train models and they will licence those models to inference companies that manage the APIs.
The inference companies need much less capital and the training companies dont need to divert resources from training to inference.
Some of the Chinese model training companies are already doing this and licencing their models to inference providers.
Re: The gap between open weights LLMs and closed source LLMs
#175Earlier quoted context omitted.
> except for some narrow use-case. I think it's entirely the opposite. For narrow use cases, like web pages and crud/GUI, the open source models don't show much of a difference.
100% agree. My impression is that the open-weight models have been drawing close-to-level at coding tasks, while Anthropic and OpenAI have been putting large amounts of effort into developing their models' abilities in other domains: legal, biomedical/science, etc. Anthropic (especially?) has also been putting more obvious resource behind optimising their harnesses - from Code to Cowork (which is kinda Code for normi…
GLM 5.2 has replaced "normie" agentic workflows previously backed by Sonnet and Opus. So I don't know. From my end it seems to me they are perfectly capable of working agenticly.
Re: The gap between open weights LLMs and closed source LLMs
#176Earlier quoted context omitted.
That only affects people in California. Whereas Fable being shut down affects people all over the world.
> That only affects people in California First they came for the Californians And I did not speak out Because I was not a Californian
Then they came for me
But it was unsuccessful
Because I was not in CaliforniaRe: The gap between open weights LLMs and closed source LLMs
#177Interesting to consider this inline with recent us export bans, could the US be squandering its lead by giving the open source, largely Chinese labs catch up (in terms of model quality available to masses), will US labs be able to maintain the lead without users being able to use their latest models?
Why do you think this matters? Not that it does or doesn't but what quality does "US WINS" or "CHINA WINS" bring to the table?
I think the issue matters (not us vs china) due to the investment and exposure normal people have to the valuations of the AI companies. It feels like the US govt could make this the pin that pops the bubble. If these companies loose their lead their value drops and the stock market tanks.
Re: The gap between open weights LLMs and closed source LLMs
#178I believe the open model party will eventually end. Perhaps because companies realize it’s too much of a commercial advantage, countries don’t want to give other countries commercial or military help, or maybe even an outright ban after someone uses an open model to guide them through how to make a bomb.
If we were going to ban technology because it helped people make bombs we wouldn't have access to much anymore.
Re: The gap between open weights LLMs and closed source LLMs
#179Frankly it does not matter if there is gap because for most practical use-cases the end user can barely perceive the difference in intelligence. On paper frontier models will be ahead of the curve but I don't think hardly anyone will be able to tell if a piece of work, say a landing page, is created with Fable or GLM and that is the point. The perceptible intelligence will reach a point beyond which it is no longer c…
> except for some narrow use-case. I think it's entirely the opposite. For narrow use cases, like web pages and crud/GUI, the open source models don't show much of a difference.
You think Web pages, crud and gui are a narrow use case?
Re: The gap between open weights LLMs and closed source LLMs
#180at first glance, these graphs are confusing
Totally agree. That first chart is just four vertical lines, I can't figure out what the hell I'm supposed to be looking at without reading the article.