be7aSystem Card: Claude Mythos Preview [pdf]
https://www-cdn.anthropic.com/53566bf5440a10affd749724787c8913a2ae0841.pdf
Combined results (Claude Mythos / Claude Opus 4.6 / GPT-5.4 / Gemini 3.1 Pro)
SWE-bench Verified: 93.9% / 80.8% / — / 80.6%
SWE-bench Pro: 77.8% / 53.4% / 57.7% / 54.2%
SWE-bench Multilingual: 87.3% / 77.8% / — / —
SWE-bench Multimodal: 59.0% / 27.1% / — / —
Terminal-Bench 2.0: 82.0% / 65.4% / 75.1% / 68.5% GPQA Diamond: 94.5% / 91.3% / 92.8% / 94.3%
MMMLU: 92.7% / 91.1% / — / 92.6–93.6%
USAMO: 97.6% / 42.3% / 95.2% / 74.4%
GraphWalks BFS 256K–1M: 80.0% / 38.7% / 21.4% / —
HLE (no tools): 56.8% / 40.0% / 39.8% / 44.4%
HLE (with tools): 64.7% / 53.1% / 52.1% / 51.4%
CharXiv (no tools): 86.1% / 61.5% / — / —
CharXiv (with tools): 93.2% / 78.9% / — / —
OSWorld: 79.6% / 72.7% / 75.0% / —
We're gonna need some new benchmarks...
ARC-AGI-3 might be the only remaining benchmark below 50%
[dead]
Opus 4.6 currently leads the remote labor index at 4.17. GPT-5.4 isn't measured on that one though: https://www.remotelabor.ai/
GPT 5.4 Pro leads Frontier Maths Tier 4 at 35%: https://epoch.ai/benchmarks/frontiermath-tier-4/
Haven't seen a jump this large since I don't even know, years?
Too bad they are not releasing it anytime soon (there is no need as they are still currently the leader).
Too bad they are not releasing it anytime soon (there is no need as they are still currently the leader).
There's speculation that next Tuesday will be a big day for OpenAI and possibly GPT 6. Anthropic showed their hand today.
That does not sound very believable. Last time Anthropic released a flagship model, it was followed by GPT Codex literally that afternoon.
My understanding is GPT 6 works via synaptic space reasoning... which I find terrifying. I hope if true, OpenAI does some safety testing on that, beyond what they normally do.
That's sounds really interesting. Do you have some hints where to read more?
A jump that we will never be able to use since we're not part of the seemingly minimum 100 billion dollar company club as requirement to be allowed to use it.
I get the security aspect, but if we've hit that point any reasonably sophisticated model past this point will be able to do the damage they claim it can do. They might as well be telling us they're closing up shop for consumer models.
They should just say they'll never release a model of this caliber to the public at this point and say out loud we'll only get gimped versions.
This is why the EAs, and their almost comic-book-villain projects like "control AI dot com" cannot be allowed to win. One private company gatekeeping access to revolutionary technology is riskier than any consequence of the technology itself.
Couldn't agree more. The "safest" AI company is actually the biggest liability. I hope other companies make a move soon.
No it isn't lol. The consequence of the technology literally includes human extinction. I prefer 0 companies, but I'll take 1 over 5.
Having done a quick search of "control AI dot com", it seems their intent is educate lawmakers & government in order to aid development of a strong regulatory framework around frontier AI development.
Not sure how this is consistent with "One private company gatekeeping access to revolutionary technology"?
More than killer AI I'm afraid of Anthropic/OpenAI going into full rent-seeking mode so that everyone working in tech is forced to fork out loads of money just to stay competitive on the market. These companies can also choose to give exclusive access to hand picked individuals and cut everyone else off and there would be nothing to stop them.
This is already happening to some degree, GPT 5.3 Codex's security capabilities were given exclusively to those who were approved for a "Trusted Access" programme.
Well don’t forget we still have competition. Were anthropic to rent seek OpenAI would undercut them. Were OpenAI and anthropic to collude that would be illegal. For anthropic to capture the entire coding agent market and THEN rent seek, these days it’s never been easier to raise $1B and start a competing lab
Describing providing a highly valuable service for money as `rent seeking` is pretty wild.
Rent seeking refers to https://en.wikipedia.org/wiki/Rent-seeking
Actually you're saying similar things:
Rent-seeking of old was a ground rent, monies paid for the land without considering the building that was on it.
Residential rents today often have implied warrants because of modern law, so your landlord is essentially selling you a service at a particular location.
It could be, formally, if they have a monopoly.
However, I’m tempted to compare to GitHub: if I join a new company, I will ask to be included to their GitHub account without hesitation. I couldn’t possibly imagine they wouldn’t have one. What makes the cost of that subscription reasonable is not just GitHub’s fear a crowd with pitchforks showing to their office, by also the fact that a possible answer to my non-question might be “Oh, we actually use GitLab.”
If Anthropic is as good as they say, it seems fairly doable to use the service to build something comparable: poach a few disgruntled employees, leverage the promise to undercut a many-trillion-dollar company to be a many-billion dollar company to get investors excited.
I’m sure the founders of Anthropic will have more money than they could possibly spend in ten lifetimes, but I can’t imagine there wouldn’t be some competition. Maybe this time it’s different, but I can’t see how.
The thing is that the current models can ALREADY replicate most software-based products and services on the market. The open source models are not far behind. At a certain point I'm not sure it matters if the frontier models can do faster and better. I see how they're useful for really complex and cutting edge use cases, but that's not what most people are using them for.
but you are assuming that the magical wizards are the only ones who can create powerful AIs... mind you these people have been born just few decades ago. Their knowledge will be transferred and it will only take a few more decades until anyone can train powerful AIs ... you can only sit on tech for so long before everyone knows how to do it
> A jump that we will never be able to use since we're not part of the seemingly minimum 100 billion dollar company club as requirement to be allowed to use it.
> They should just say they'll never release a model of this caliber to the public at this point and say out loud we'll only get gimped
Duh, this was fucking obvious from the start. The only people saying otherwise were zealots who needed a quick line to dismiss legitimate concerns.
Honestly we are all sleeping on GPT-5.4. Particularly with the influx of Claude users recently (and increasingly unstable platform) Codex has been added to my rotation and it's surprising me.
GPT is shit at writing code. It's not dumb - extra high thinking is really good at catching stuff - but it's like letting a smart junior into your codebase - ignore all the conventions, surrounding context, just slop all over the place to get it working. Claude is just a level above in terms of editing code.
This has been my experience. With very very rigid constraints it does ok, but without them it will optimize expediency and getting it done at the expense of integrating with the broader system.
My favorite example of this from last night:
Me: Let's figure out how to clone our company Wordpress theme in Hugo. Here're some tools you can use, here's a way to compare screenshots, iterate until 0% difference.
Codex: Okay Boss! I did the thing! I couldn't get the CSS to match so I just took PNGs of the original site and put them in place! Matches 100%!
And as a bonus: GPT is slow. I’m doing a lot of RE (IDA Pro + MCP), even when 5.4 gives a little bit better guesses (rarely, but happens) - it takes x2-x4 longer. So, it’s just easier to reiterate with Opus
Not my experience. GPT 5.4 walks all over Claude from what I've worked with and its Claude that is the one willing to just go do unnecessary stuff that was never asked for or implement the more hacky solutions to things without a care for maintainability/readability.
But I do not use extra high thinking unless its for code review. I sit at GPT 5.4 high 95% of the time.
Yes, it's becoming clear that OpenAI kinda sucks at alignment. GPT-5 can pass all the benchmarks but it just doesn't "feel good" like Claude or Gemini.
An alternative but similar formulation of that statement is that Anthropic has spent more training effort in getting the model to “feel good” rather than being correct on verifiable tasks. Which more or less tracks with my experience of using the model.
Very different experience for me. Codex 5.3+ on xhigh are the only models I've tried so far that write reasonably decent C++ (domains: desktop GUI, robotics, game engine dev, embedded stuff, general systems engineering-type codebases), and idiomatic code in languages not well-represented in training data, e.g. QML. One thing I like is explicitly that it knows better when to stop, instead of brute-forcing a solution by spamming bespoke helpers everywhere no rational dev would write that way.
Not always, no, and it takes investment in good prompting/guardrails/plans/explicit test recipes for sure. I'm still on average better at programming in context than Codex 5.4, even if slower. But in terms of "task complexity I can entrust to a model and not be completely disappointed and annoyed", it scores the best so far. Saves a lot on review/iteration overhead.
It's annoying, too, because I don't much like OpenAI as a company.
(Background: 25 years of C++ etc.)
Are these fair comparisons? It seems like mythos is going to be like a 5.4 ultra or Gemini Deepthink tier model, where access is limited and token usage per query is totally off the charts.
There are a few hints in the doc around this
> Importantly, we find that when used in an interactive, synchronous, “hands-on-keyboard”
pattern, the benefits of the model were less clear. When used in this fashion, some users perceived Mythos Preview as too slow and did not realize as much value. Autonomous, long-running agent harnesses better elicited the model’s coding capabilities. (p201)
^^ From the surrounding context, this could just be because the model tends to do a lot of work in the background which naturally takes time.
> Terminal-Bench 2.0 timeouts get quite restrictive at times, especially with thinking models, which risks hiding real capabilities jumps behind seemingly uncorrelated confounders like sampling speed. Moreover, some Terminal-Bench 2.0 tasks have ambiguities and limited resource specs that don’t properly allow agents to explore the full solution space — both being currently addressed by the maintainers in the 2.1 update. To exclusively measure agentic coding capabilities net of the confounders, we also ran Terminal-Bench with the latest 2.1 fixes available on GitHub, while increasing the timeout limits to 4 hours (roughly four times the 2.0 baseline). This brought the mean reward to 92.1%. (p188)
> ...Mythos Preview represents only a modest accuracy improvement over our best Claude Opus 4.6 score (86.9% vs. 83.7%). However, the model achieves this score with a considerably smaller token footprint: the best Mythos Preview result uses 4.9× fewer tokens per task than Opus 4.6 (226k vs. 1.11M tokens per task). (p191)
> Claude Mythos Preview is, on essentially every dimension we can measure, the best-aligned model that we have released to date by a significant margin. We believe that it does not have any significant coherent misaligned goals, and its character traits in typical conversations closely follow the goals we laid out in our constitution. Even so, we believe that it likely poses the greatest alignment-related risk of any model we have released to date. How can these claims all be true at once? Consider the ways in which a careful, seasoned mountaineering guide might put their clients in greater danger than a novice guide, even if that novice guide is more careless: The seasoned guide’s increased skill means that they’ll be hired to lead more difficult climbs, and can also bring their clients to the most dangerous and remote parts of those climbs. These increases in scope and capability can more than cancel out an increase in caution.
https://www-cdn.anthropic.com/53566bf5440a10affd749724787c89...
"We want to see risks in the models, so no matter how good the performance and alignment, we’ll see risks, results and reality be damned."
i mean, to be fair, these are professional researchers.
i'm very inclined to trust them on the various ways that models can subtly go wrong, in long-term scenarios
for example, consider using models to write email -- is it a misalignment problem if the model is just too good at writing marketing emails?? or too good at getting people to pay a spammy company?
another hot use case: biohacking. if a model is used to do really hardcore synthetic chemistry, one might not realize that it's potentially harmful until too late (ie, the human is splitting up a problem so that no guardrails are triggered)
Translation: yay, more paternalism.
Anthropic always goes on and on about how their models are world changing and super dangerous like every single time they make something new they say its going to rewrite everything and scary lmao
funny because they do it every time like clockwork acting like their ai is a thunderstorm coming to wipe out the world
I've long maintained that the real indicator that AGI is imminent is that public availability stops being a thing. If you truly believed you had a superhuman, godlike mind in your thrall, renting it out for $20/month would be the last thing you would choose to do with it.
Priced at $25/$125 per million input/output token. Makes you wonder whether it makes more financial sense to hire 1-2 engineers in a cheap cost of living country who use much cheaper LLMs
Slack user: [a request for a koan]
Model: A student said, "I have removed all bias from the model." "How do you know?" "I checked." "With what?"
Goes hard