Claude Fable 5 review: what the new Mythos model gets right (and very wrong)

**Claire Vo** (0:00)
It's here, the model, the myth, the legend, Mythos from Anthropic has finally dropped. Well, baby Mythos, we're calling it Fable 5, and this new model is crushing benchmarks, but the question is, can it crush my backlog? I got early access to the model, and of course, I have my own opinions on where it does really well, where it needs a little work, and the question on everyone's mind, does it live up to the terrifying marketing hype? Let's get to it. Okay, let's talk about what Anthropic is telling us about this model, and then we'll get into what I think about it. So this is Claude Fable 5, the first Mythos class intelligence model to reach GA. Now, if you haven't been paying attention, Anthropic has been marketing slash scaring slash warning us about the unbelievable capabilities of Mythos, and it is finally here. Now, they had originally been rolling this out with a couple select companies. I got early access to test what I thought of the model, but you have to know, this is not Mythos, capital M, big Mythos. This is, they mean Mythos. This is Fable. And so it's going to have some guardrails on it, in particular around cybersecurity exercises and biology exercises. Now, good news, your girl's working on PRDs. She's shipping SAS. She's not working on biology quite yet, although give me a little time and some time to experiment. Maybe I'll get there. So this is really going to be focused on what the everyday user, what the everyday software engineer is going to think about when they're using this model. Although I did run into some things that I suspect are a result of the tuning and training of this particular model to be extra safe. Now, quick, it's not cheap. It's $10 per input token and $50 per output token. It's going to be a new tier above Opus. And so if you're going to use this model, you're going to pay the price.
So what is Anthropic saying? Basically, it's a completely new model class. So we had Sonnet, we had Opus, and now we have Mythos, the first of which is Fable 5 It's completely state-of-the-art. It is exceeding every benchmark they tested by a significant amount. This 80% on SWBench Pro, you'll look at that compared to some of the more recent models that have come out. Very, very good benchmark performance. And then they're saying it's really good for long, complex tasks. Now, what are some things that earlier models couldn't do that they are saying now that Fable 5 can do? It's very autonomous, including running days-long asynchronous tasks. It's really an engineer's engineer. And that's some of the downside I experienced with this model. I'm going to show you a very specific example of where you don't want an engineer doing your work with an engineer's point of view.
Proactive. It's very good at vision, exceptionally good at vision. This is a place where I actually really loved the model. And you know me, I'm pretty critical of models, but I did see a step ahead of vision, so that's something we're going to dive into. And then effort, it works hard, it builds harder, it verifies more, it's built for ambitious work. Now, guess what it also can do? It can consume those tokens. So Anthropica said it consumes rate limits and tokens at about 2x the rate of other models. So again, this is a big boy model and it's going to consume tokens. And some of the things that it's good at, even some things that they have done in the Harness, seem like they're intentionally or not token consumers. So we're going to keep an eye out on costs and eye out on efficiency when using this model. Again, talking about long running tasks, Fable 5 is supposed to be able to run four days. So doing long running planning, being able to spin up subagents, and I show a little bit about dynamic workflows, which are different architectures of subagents and holding multi-day sessions. Now, I have done probably day days long sessions with other models. I didn't have Fable for many days, so I cannot verify that it ran for days. I did get it to run, however, for several hours on some tasks that may or may not have merited that several hour effort, but it definitely seems like it has both the hardness and the intelligence capability to run for a very long time, if that's appropriate for your task. Now here's your pros and here's your cons. They explicitly say that Fable works like a seasoned engineer. Unfortunately, if you have worked with a seasoned engineer, you know there's good to this and you know there's bad to this. So it is very complete in its investigation. It's definitely going to go search out all the corners. It's definitely going to think about how it can be 120 percent sure that it's shipping the right thing. But guess what? That's not always in service of launching, and that's honestly not always in service of building a great product. So while you can give it a goal and it will be very autonomous and it will be very thorough, honestly, sometimes you want like a slightly less thorough engineer.