i haven't used any Anthropic models since Jan / Feb so i was excited to unleash fable on a bunch of benchmarks and a few of my most complicated repos. so far, it seems like a huge improvement over opus, especially for claude code expert use cases but still not on par with gpt 5.5 xhigh for my specific use cases. in fact, its pretty on par with my fine tuned k2.6 outside of the new claude code features . the areas where it seems to excel are large multi part reviews (it caught a handful of really subtle and complex bugs) and multi-step long running tasks. i kept it away from my research / training and infra code for obvious reasons, so this is 'normal' software dev specific .

overall, solid effort and a huge improvement over the most recent opus, but not pushing the frontier in any meaningful ways (at least that i can see so far). i will probably use it for the rest of the day just to be sure and then move back to 80% k2.6 and 20% gpt 5.5 xhigh

Quotes from the release today:

'Using Mythos 5, our internal protein design experts accelerated aspects of the drug design process by around ten times. In one example, they found that Mythos 5, with protein design and bioinformatics tools but no human assistance, matches or beats skilled human operators. In doing so, the model executes all of the tasks that are normally completed by a scientist: choosing binding sites, selecting and running protein design tools, and recovering from failures along the way.'

'During early testing, Stripe reported that Fable 5 compressed months of engineering into days. In a 50-million-line Ruby codebase, the model performed a codebase-wide migration in a day that would otherwise have taken a whole team over two months by hand.'

'Mythos 5 is our first model to consistently produce novel, compelling scientific hypotheses. In blinded head-to-head comparisons against Opus-class models, our scientists preferred Mythos’s molecular biology hypotheses ~80% of the time, and have advanced several to experimental evaluation. In the meantime, one Mythos hypothesis—a novel mechanism for an E. coli protein—was corroborated in a study from a lab independently working on the same problem.'

'Mythos 5 conducted novel genomics research in over a week of largely autonomous work. It assembled single-cell data for millions of cells spanning 138 animal species and designed and trained a custom machine learning model to identify cells performing the same role in even distantly related organisms. With only high-level human input, Mythos 5’s trained model outperformed a recent model published in the journal Science—despite being 100 times smaller. We intend to publish these results in the coming months.'