This was my exact takeaway after my experience using it all weekend, and I used it a lot working on a non-trivial personal project (full stack with a Golang backend with multiple services and a React/TS frontend, not quite greenfield but still early-ish in development).
My weekly quota resets Sunday morning, so Saturday morning I upgraded to a 20x Max plan which also reset my quota. I burned an entire week of Fable credits on Saturday, my quota reset again, then I burned another week of Fable credits on Sunday. Both days were a mix of building features, reviewing code, fixing bugs, adding tests, etc, so a decent mix of real world usage.
The main takeaway for me is that while Fable is definitely a better model, the improvements from the model itself feel like maybe 10%, like this could have easily been Opus 5 or even 4.9 without all the marketing theater around Mythos and no one would have thought anything of it. The rest of the improvements came from harness/system prompt and effort level changes so that Fable uses significantly more tokens/effort/sub-agents at lower levels than Opus does (which of course is entirely controlled by Anthropic at the harness level and doesn't really have anything to do with the model itself).
In my estimation based on those 2 days of work (or two weeks of work depending on how you look at it), Fable Medium is somewhere above Opus Ultracode in token and sub-agent usage on any non-trivial task (Opus Ultracode uses workflows more than sub-agents, but it's a similar idea). Fable Medium will quickly spawn 6 agents in parallel, each quickly using 150-250k tokens, then will use 300-500k or more tokens in its own context. Fable High uses even more as it seems to default to 8 sub-agents instead of 6 and more tokens in its own context). I didn't dare try Extra, Max, or god forbid Ultracode as I didn't want to burn all my tokens on one prompt. Of course this is situational, it won't fan out so many for smaller tasks, but the whole point was testing larger tasks that I previously would have used Opus Extra/Max/Utracode on.
I really don't like how Anthropic is obfuscating their model performance by playing with effort levels. They did the same thing between Opus 4.5 and 4.8 to show a bigger performance gain for each point release than they really had (especially after 4.6 IIRC), so you can't even compare the same model apples to apples let alone a new model. Obviously they do it so they can market big improvements with new releases, but its pretty clear we're at the top of the S curve on model development at this point and are now brute forcing improvements via higher token usage (I mean Opus 4.5 came out almost a year ago, and the latest Opus and now Fable models are only marginally better while using way more tokens/cost...same on the OpenAI side with GPT 5 from what I can tell though I haven't used Codex much I have used the GPT model APIs a lot).
I also did an N=1 test with the same prompt doing a large non-trivial change to the codebase (migrating from Sqlite3 to Postgres) with both Fable Medium and Opus Ultracode, then had a new Fable session compare the two PRs...it decided Opus’s was much better! I can link a Gist with the review if anyone is interested, but I can't share the code as it's a private repo. I really figured Fable would bias to favor its own code, but I guess not. And Opus costed less (in tokens and subscription limits) and took roughly the same time (though you can’t really measure time since it depends entirely on how many GPUs Anthropic allocates at that moment which constantly fluctuates due to usage, plus Fable seemed to have been getting way more allocation than Opus during this test period as Opus was running unusually slow all weekend while Fable was ripping though tokens).
Also on a different long running review task using Fable High in Auto mode (exactly the kind of use case Anthropic promotes for Fable) where it fanned out a ton of sub-agents then collated and reviewed all of their fixes it completely lost the plot (while burning something like 20% of an entire week's Fable tokens in the process over like 1-2 hours). Its PR ended up having a broken Frontend test, it incorrectly thought it couldn't run the Playwright E2E tests (different from the Frontend CI) in the cloud environment due to a Docker dependency they explicitly don't have, and when attempting to get it to fix its issues it introduced new ones and overlooked others. The usual LLM failure case for long running tasks, no different from Opus or any other model. I had to have its PR re-reviewed in a new Fable Medium session to fix it up, which it did fairly easily (I'm sure Opus could have done just as well for much cheaper).
That test and that review session definitely reduced my FOMO a lot, on top of just my general experience with Fable Medium doing all kinds of tasks. They're clearly brute forcing like 90% of the perceived improvements in real world usage (and I'm sorry but 1-shotting toy examples where it seems to do much better than Opus is not real world usage).
Since most of the improvements basically just boil down to "every effort level is Ultracode, but much more expensive and possibly worse results"...I'm just going to use Opus on Ultracode for those types of tasks and keep using Opus's lower effort levels for smaller tasks. Once they eventually add Fable back to subscription plans I might use it sometimes, but from my experience this weekend the improvements are absolutely not in line with the cost increase and I'm not willing to burn a whole week's tokens in a day just to use it when I can use Opus all week without hitting my limit.
Oh and one interesting observation, I never got kicked back to Opus by the security guardrails as far as I know (a friend who was getting kicked out a lot confirmed they do inform you and I never had that happen). I was even doing a lot of reviews for code correctness and bug fixes which I thought might trigger the protections, but never did, though I never explicitly prompted it to look for security issues or vulns.