Comment by mekpro
2 hours ago
It’s clear that Anthropic has run out of the compute capacity needed to serve Mythos publicly.
They’re using security concerns to mask their inability to deliver the model at scale, while still trying to maintain their lead over OpenAI. As a result, they’ve chosen to release it privately under the banner of an “ethical” rollout.
It is not "clear", as your comment suggests, it's hidden. Which is semantically the opposite of clear. Regarding your theory, might be true, might be false. But it's highly speculative.
They started Glasswing before they struck that $1.25B/month deal with xAI/SpaceX for their (notoriously dirty) Memphis data centers.
So they have a whole lot more compute now than they did last month.
Yes, 300 MW from SpaceX helps a lot, but I think that’s mainly to support Opus demand, which has grown faster than expected. If Mythos is roughly 5× more expensive to serve than Opus, as the pricing suggests, then 300 MW is nowhere near enough to enable large-scale deployment of Mythos.
As an ordinary developer who relies on a $20–$200/month subscription, I feel disappointed by the release of a paper describing a model that I can’t actually use.
Ok but they can easily upsell this to enterprise customers at a market price reflective of their capacity constraints. Big corps would pay it, this is clearly a major update.
But that compute might not be available to then long term. Hard to make big moves with a contract like that.
I don't know if any of the big AI labs have confidence in planning for the long term.
For all they know they'll find a new optimization that lets them serve Opus class models for half the computing cost next month. Or someone will invent the next OpenClaw and demand will 10x over night.
The security concerns argument would have worked better if a forum full of people hadn't promptly obtained access by the extremely sophisticated tactic of guessing its URL...
So why is OpenAI also releasing 5.5-Cyber in a private manner? Are they also out of compute?
Probably. This is an 8-12 trillion-parameter model, which is why it costs so much, that is also a major reason, besides RL and synthetic data, why it suddenly gained these new capabilities. They claim it was not fine-tuned or trained specifically for cybersecurity, but is instead a general purpose model.
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