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I find this line of reasoning highly dubious.

Yes, Anthropic is compute constrained, even after the SpaceX Colossus deal.

But supply constraints are the normal operating mode of any market. Anthropic could choose to serve whatever models it pleases at whatever price points it chooses and let the market decide where the value is.

If Mythos at $X overwhelms their capacity, they could just charge $X+1. If still overwhelmed, there are larger prices as well.

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The question is, will anyone pay enough for Mythos to offset the opportunity cost of offering that much Opus? You don't want to end up in a spot where you don't have enough compute and your service's reliability degrades to an unusable state like xAI.
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No insider info, but just wanted to mention that pricing signals things too. If Mythos is only servable at $X*Y dollars and isn’t Y times better than $X of compute at another provider, it’s quite possible that affects the IPO price negatively versus the halo of having the worlds most expensive model that is “too powerful to release” unpriced and unbenchmarked.

I think that most people at Anthropic are true believers from my interactions with them so I don’t believe this theory anecdotally. The simplest explanation is that it really is taking a while to gain confidence they won’t be used for a spree of bad cyber attacks. Knowing how long it takes institutions to fix security issues when filed by humans I would be more suprised if this wasn’t the case.

But I would forgive anyone who did think it was deliberately sandbagged; given the staggering sums at play, true believers might believe the ends justify the means to a little “marketing” like this.

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Sort of, but valuation models depend on X being in a certain range. If it > this range, revenue and therefore valuation are impacted.
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And then the bubble would collapse. Corps are already putting limits on token usage across the board because of costs. Increasing costs would significantly contract the hype bubble.
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I had to patch my Linux boxes daily at some point in the past couple months. I don’t want Mythos to be publicly released for as long as it is economically feasible for Anthropic. I hope they have a gentleman’s agreement with OpenAI and DeepMind about this, too.

Chinese labs will force their hands, until then let’s hope maximum number of projects get patched at a reasonable pace.

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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.
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All of us, including you, know that he is not saying "they are being transparent." When someone says "it's clear that..." in this way they're saying "It's clear to us what is really happening here.
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It's not clear, there is no tangible proof that Mythos is not released because they don't have compute power to serve it. Saying that would imply that the "too dangerous" is a lie. Nobody has proof. It can feel "clear" for you, but it's not. Hence, I correct it.
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Yes I got how they used the phrase. And it was wrong, so I wanted to react. Thanks for your addition, it dissipates any doubt on the intention of OP: he thinks Anthropic is hiding the lack of power by pretending it's too dangerous. But he is wrong to assume that without proof, hence my reaction.
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Agreed, but I'm talking about how they are, very clearly, using the phrase.
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The not clear comment is valid by either interpretation.

To a lot of us it’s not clear that’s what’s happening. It’s speculation and one possibility.

It may also be a secondary consideration and not the primary gating factor.

Anthropic has had their missteps but it’s still plausible to take what they say at face value.

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I agree, saying "it's clear" when at best, "it's plausible" doesn't let the conversation happen. And pretending to know what is going on behind the scene, anon on HN is not credible
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Why do you think that? All these rumors about compute constraint just seem like speculation and not based on any data or information. All they would need to do is increase their prices to free up compute capacity.
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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.

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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.

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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.
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But that compute might not be available to then long term. Hard to make big moves with a contract like that.
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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.

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So why is OpenAI also releasing 5.5-Cyber in a private manner? Are they also out of compute?
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OpenAI has been pulling this marketing trick for years. Remember how GPT-3 was too dangerous to release? It's also probably bad PR if script kiddies have access to GPT model with no guardrails even if it doesn't enable any significant attacks.
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I suppose you meant GPT-2, but for years? Did they say the same about subsequent models?
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I bet Huawei and co would be happy to sell them some cheapo chips for inference!
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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...
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Also, they just want to jack up the price by creating sensation.
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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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