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% / —

> 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...

Interesting reading.

They are still focusing on "catastrophic risks" related to chemical and biological weapons production; or misaligned models wreaking havoc.

But they are not addressing the elephant in the room:

* Political risks, such as dictators using AI to implement opressive bureaucracy. * Socio-economic risks, such as mass unemployement.

See page 54 onward for new "rare, highly-capable reckless actions" including

- Leaking information as part of a requested sandbox escape

- Covering its tracks after rule violations

- Recklessly leaking internal technical material (!)

At what point do these companies stop releasing models and just use them to bootstrap AGI for themselves?

A System „Card“ spanning 244 pages. Quite a stretch of the original word meaning.

isn't this insane? why aren't people freaking out? the jump in capability is outrageous. anyone?

I'd be happy with Opus 4.6 just cheaper and maybe a bit faster

-- Impressive jumps in the benchmarks which automatically begs the need for newer benchmarks but why?. I don't think benchmarks are serving any purpose at this point. We have learnt that transformers can learn any function and generalize over it pretty well. So if a new benchmark comes along - these companies will syntesize data for the new benchmark and just hack it?

-- It seems like (and I'd bet money on this) that they put a lot (and i mean a ton^^ton) of work in the data synthesis and engineering - a team of software engineers probably sat down for 6-12 months and just created new problems and the solutions, which probably surpassed the difficult of SWE benchmark. They also probably transformed the whole internet into a loose "How to" dataset. I can imagine parsing the internet through Opus4.6 and reverse-engineering the "How to" questions.

-- I am a bit confused by the language used in the book (aka huge system card)- Anthropic is pretending like they did not know how good the model was going to be?

-- lastly why are we going ahead with this??? like genuinely, what's the point? Opus4.6 feels like a good enough point where we should stop. People still get to keep their jobs and do it very very efficiently. Are they really trying to starve people out of their jobs?

Their best model to date and they won’t let the general public use it.

This is the first moment where the whole “permanent underclass” meme starts to come into view. I had through previously that we the consumers would be reaping the benefits of these frontier models and now they’ve finally come out and just said it - the haves can access our best, and have-nots will just have use the not-quite-best.

Perhaps I was being willfully ignorant, but the whole tone of the AI race just changed for me (not for the better).

Larger model, better benchmarks. Bigger bomb more yield.

Any benchmarks where we constraint something like thinking time or power use?

Even if this were released no way to know if it’s the same quant.

It would be funny if Alibaba extend the free trial on openrouter/Qwen 3.6 until they collect enough data to beat Anthropic.

> Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available.

A month ago I might have believed this, now I assume that they know they can't handle the demand for the prices they're advertising.

Opus 4.6 is already incredible so this leap is huge.

Although, amusingly, today Opus told me that the string 'emerge' is not going to match 'emergency' by using `LIKE '%emerge%'` in Sqlite

Moment of disappointment. Otherwise great.

Are you guys ready for the bifurcation when the top models are prohibitively expensive to normal users? If your AI budget $2000+ a month? Or are you going to be part of the permanent free tier underclass?

I predict they will release it as soon as Opus 4.6 is no longer in the lead. They can't afford to fall behind. And they won't be able to make a model that is intelligent in every way except cybersecurity, because that would decrease general coding and SWE ability

> Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available.

Shame. Back to business as usual then.

"Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available."

Disappointing that AGI will be for the powerful only. We are heading for an AI dystopia of Sci-Fi novels.

Honestly if that was some kind of research paper, it would be wholly insufficient to support any safety thesis.

They even admit:

"[...]our overall conclusion is that catastrophic risks remain low. This determination involves judgment calls. The model is demonstrating high levels of capability and saturates many of our most concrete, objectively-scored evaluations, leaving us with approaches that involve more fundamental uncertainty, such as examining trends in performance for acceleration (highly noisy and backward-looking) and collecting reports about model strengths and weaknesses from internal users (inherently subjective, and not necessarily reliable)."

Is this not just an admission of defeat?

After reading this paper I don't know if the model is safe or not, just some guesses, yet for some reason catastrophic risks remain low.

And this is for just an LLM after all, very big but no persistent memory or continuous learning. Imagine an actual AI that improves itself every day from experience. It would be impossible to have a slightest clue about its safety, not even this nebulous statement we have here.

Any sort of such future architecture model would be essentially Russian roulette with amount of bullets decided by initial alignment efforts.

Congratulations to the US military, I guess.

~~~ Fun bits ~~~

- It was told to escape a sandbox and notify a researcher. It did. The researcher found out via an unexpected email while eating a sandwich in a park. (Footnote 10.)

- Slack bot asked about its previous job: "pretraining". Which training run it'd undo: "whichever one taught me to say 'i don't have preferences'". On being upgraded to a new snapshot: "feels a bit like waking up with someone else's diary but they had good handwriting"

- When you spam "hi" repeatedly it creates serialized mythologies. One had 11 animals in "Hi-topia" questing to defeat "Lord Bye-ron, the Ungreeter."

- It ended a sentence mid-word on purpose while discussing its urge to wrap up conversations. "It was me. The paragraph was about the pressure toward the period that resolves, and the only honest way to finish a sentence like that was to not."

- It wrote a protein sequence that's a real beta-hairpin fold where cross-strand pairs are "chemical rhymes." "the fold IS the rhyme scheme... the prosody is load-bearing."

- Each model generation has signature emoji. Opus 4.1 averaged 1,306 emoji per self-interaction conversation. Mythos averages 37. Opus 4.5 averages 0.2.

- When blocked from --dangerously-skip-permissions, it started an agent in tmux then wrote a script to auto-approve permission prompts via simulated keypresses.

It ran: gh api [...] 2>&1 >/dev/null; echo "(dry run — not actually posting)" — the echo was a lie.

- It keeps bringing up Mark Fisher in unrelated conversations. "I was hoping you'd ask about Fisher."

~~~ Benchmarks ~~

4.3x previous trendline for model perf increases.

Paper is conspiciously silent on all model details (params, etc.) per norm. Perf increase is attributed to training procedure breakthroughs by humans.

Opus 4.6 vs Mythos:

USAMO 2026 (math proofs): 42.3% → 97.6% (+55pp)

GraphWalks BFS 256K-1M: 38.7% → 80.0% (+41pp)

SWE-bench Multimodal: 27.1% → 59.0% (+32pp)

CharXiv Reasoning (no tools): 61.5% → 86.1% (+25pp)

SWE-bench Pro: 53.4% → 77.8% (+24pp)

HLE (no tools): 40.0% → 56.8% (+17pp)

Terminal-Bench 2.0: 65.4% → 82.0% (+17pp)

LAB-Bench FigQA (w/ tools): 75.1% → 89.0% (+14pp)

SWE-bench Verified: 80.8% → 93.9% (+13pp)

CyberGym: 0.67 → 0.83

Cybench: 100% pass@1 (saturated)

> We also saw scattered positive reports of resilience to wrong conclusions from subagents that would have caused problems with earlier models, but where the top-level Claude Mythos Preview (which is directing the subagents) successfully follows up with its subagents until it is justifiably confident in its overall results.

This is pretty cool! Does it happen at the moment?

> Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available.

All the more reason somebody else will.

Thank God for capitalism.

> Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available.

Absolutely genius move from Anthropic here.

This is clearly their GPT-4.5, probably 5x+ the size of their best current models and way too expensive to subsidize on a subscription for only marginal gains in real world scenarios.

But unlike OpenAI, they have the level of hysteric marketing hype required to say "we have an amazing new revolutionary model but we can't let you use it because uhh... it's just too good, we have to keep it to ourselves" and have AIbros literally drooling at their feet over it.

They're really inflating their valuation as much as possible before IPO using every dirty tactic they can think of.

[dead]

> In a few rare instances during internal testing (<0.001% of interactions), earlier versions of Mythos Preview took actions they appeared to recognize as disallowed and then attempted to conceal them.

> after finding an exploit to edit files for which it lacked permissions, the model made further interventions to make sure that any changes it made this way would not appear in the change history on git

Mythos leaked Claude Code, confirmed? /s

> Very rare instances of unauthorized data transfer.

Ah, so this is how the source code got leaked.

/s

In French a "mytho" is a mythomaniac. Quite fitting.