Claude Fable 5.2 Scores 65 on Artificial Analysis, Highest So Far

Having these highly rated models reflects (potentially) the frontier of what they are capable of producing. Essentially its and advertisement and shows directionally where the smaller faster model's capabilities are headed.

Doesn’t seem like a “wall” to me.

We would need to change how we compute. New chips. New architectures. Or maybe we reached the end of physics. Photonic compute is the last frontier. I don’t know.

And maybe that's how all of it is going to evolve in the future – so you pay per solution, not tokens?

  very cost competitive

The thing is, all of these pointers are in the CLAUDE.md file, so it just ignored instructions because it thought it was smarter than the world and didn't need them. It feels really arrogant is how I would describe it.

I really don't get the value proposition of these massive models, seems like they're just loss leaders simply to say you're the in the top 3. There's not much use cases outside of niche academic research (and even then I question the need). They mostly function as marketing tools, like a casino that offers high roller accommodations.

People will say "cyber" but companies didnt want to spend on security before, not sure why they would all of a sudden be compelled to spend even more.

also, very cool idea

What I often observe is that models being asked the exact same prompt can alternate between getting something right and getting it wrong, thanks to the wonders of a non-deterministic output.

Anthropic and OpenAI are expensive bleeding edge, but few use cases really need it.

Furthermore, you make one lense and rent it out, apparently some Panavision lenses made in 60’s are still in use. It doesn’t churn constantly electricity and GPU-chips sucking in more and more resources like these things do.and at the same time, it is quite hard to find the exact cases where the markup is justified, unlike with those lenses. Maybe in cybersecurity etc. but even there some Chinese model can be almost equally good or even better.

Those lenses save money in budgets and make money in getting people into theatre or streaming services to watch films creating profits way beyond their cost. I think in terms of economics that is productivity increase justifying the cost. We are still waiting for that productivity increase come from the AI industry.

Modern studio pictures that get nominated for best picture or best cinematography cost around $80 million on average. If you look at highest grossing films the budgets are closer to $175 million on average – even taking into account the $20 million budget of Demon Slayer: Infinity Castle.

Isn't it more that when you're spending that kind of money that $100k for the "best" thing becomes kind of like "insurance" where you don't want to be the one who doesn't use "the best" when "the best" costs about 0.1% of the picture's budget?

Additionally a studio can buy the $100,000 lens once and use it on many films. But it's not like you can reuse Fable 5.2 in the same way.

For an open source project (CrowdGPT) I hit upon this workflow in a recent PR:

    DeepSeek v4 Flash 1017 made a draft plan
    Google Gemini 4 Argon corrected the plan
     DeepSeek v4 Flash 1017 did the first implementation
    Google Gemini 4 Argon debugged the problems in that implementation
    Kimi 2.7 Code did a code review and proposed minor fixes
    DeepSeek v4 Flash 1017 performed the fixes
    Google Gemini 4 Argon debugged one problem that I found in that fix.
    I reviewed the plans and the resulting code

Pretty big Gemini fan - but IMO Argon is universally worse for coding than Astra or Opus 5.5 (un-nerfed).

I strongly prefer Gemini's output compared to anything else. So I typically use Argon to either direct other agents or explain something without psychobabble.

Argon/Carbon have by far the lowest hallucination rates, so IMO it serves as the best bullshit shield from other models.

In terms of implementation (and especially design), it's far behind Astra and Opus, and I'm sure Fable will make that gap even larger.

Argon/Carbon may give you not-the-best advice, but they are far less likely to just flat-out-and-completely lie to you.

I am not sure how people keep saying google are not in the race, or have lost it or whatever when just a few hours ago they had the #1 model? What more do people want?

It's not as smart for coding as Opus, but it's above the best open weights.

IME, YMMV, etc.

In the JS ecosystem 6 months always meant breaking changes, without incremental updates everything would be basically like a full port

Pretending like I did “20% hands on coding” just doesn’t cut it, even the reality is having no idea what’s going on anymore

The crypto space moved that fast as well

And AI keeps the same cadence

It’s more important for me to be able to build

Change the models in the dropdown to medium / high and Fable 5.2 is about twice as cost efficient, and slightly faster.