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No, GPTCyber is specifically trained for cybersecurity, and GPT-5.5-pro is just an ensemble of many subagents, not an actual model.

Mythos is simply a much bigger model in terms of parameters and I don't think OpenAI will have anything of its size anytime soon (My theory is that OpenAI had given up on scaling up parameters after GPT4.5 flopped).

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how do you know gpt-5.5-pro is an ensemble? if it is, then how did OpenAI do it? why no other company has been able to pull it off?

It's pretty much confirmed by OpenAI here [1].

> We generally treat GPT-5.5’s safety results as strong proxies for GPT-5.5 Pro, which is the same underlying model using a setting that makes use of parallel test time compute.

And Gemini also provides something similar. Gemini Deep Think models are pretty much the same thing [2]. As to why no other company uses this, I don't really know. Maybe compute constraints?

[1] https://deploymentsafety.openai.com/gpt-5-5

[2] https://deepmind.google/models/gemini/deep-think/

Plenty of other companies do this. Meta Muse Spark has a "Contemplating" which is this. Kimi had this on their website too, IIRC.

Interesting, but how do they "combine" the results of all those parallel agents? How do they know which parts of each agent response is signal vs noise?

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