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Before getting too excited, take a look at the intelligence vs cost matrix: https://artificialanalysis.ai/models?intelligence-index-toke...
5.6 Sol (max) being cheaper than all of these is wild, considering how good the output is too
Max is lot of extra reasoning. I wonder how many fewer tasks it solves on high. I bet that costs quite a lot less.
That index really needs harder tasks so that it's not just a benchmark of what model is cheapest
On my end, Opus 5 is Haiku level vs. Opus 4.8 (good) and Fable (superb).

Gets confused by permission prompts, cannot debug a failing test it caused (Opus 4.8 got it right after, without tens of rounds "thinking").

Very interesting that one of the components is "AA-Omniscience Index"

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer.

This seems to be a good proxy for param size/density and the ranking breaks down as such: Claude Fable 5 (with fallback), Gemini 3.1 Pro Preview, Claude Opus 5 (Max), Grok 4.6 (high), Gemini 3.6 Flash, GPT 5.6 Sol (Max)

I've thought for a while that Gemini 3.x has 'big model smell'

#1 in a very close race is way less useful when you have to walk on eggshells to avoid triggering censorship (“safeguards”) that either refuse or knock it down to another model. I’ve almost completely stopped using Claude (except some legacy workflows) for this reason, reliability matters more than scoring 61 instead of 57. To me Claude is the most compromised and unreliable model (between the censorship and the id checking - which I have not experienced personally), it’s not worth whatever slight benchmaxxing they did for the latest release.
The more interesting finding is that it's still the second most expensive model (after Fable 5) by a long shot.

At least two models (GPT-5.6, Kimi K3) match its score (~1-2% diff) for half the cost.

I didn't like it as much as fable. The coding style was a bit different and it way overbuilt the thing I asked from it.
I'd be curious to see the results, especially with some models having 1.5m and 2m context sizes, if the first 75% of the context was filled with unrelated info.
Why do I find it dummer/even more superficial than opus 4.8? It just continued a session and I had to stop it because it become obviously “lost”
I don't have a horse in this race, but to me this makes GPT-5.6 Sol Max look better. It is about half the cost for nearly the exact same performance. It just goes to show how expensive Fable really is when Opus 5 is still this expensive relative to GPT 5.6.
What's interesting is this:

The top AI models by Intelligence Index are: 1. Claude Opus 5 (Adaptive Reasoning, Max Effort) (61), 2. Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) (60), 3. Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) (60), 4. GPT-5.6 Sol (max) (59), and 5. Claude Opus 5 (Adaptive Reasoning, High Effort) (59).

Which means Opus5 at Xhigh is still smarter than Sol at max, and Opus5 at High is equal to Sol at max.

That would make Opus5 High same as Sol max, and now I wonder what the price and speed difference between those is?

I posted this before but I have a really simple shell tool to keep up with these charts over at

https://github.com/day50-dev/aa-eval-email

This also works

$ curl day50.dev/art-analysis.sh | bash

Artificial analysis knows about my tool and I'm working with them on getting their API improved.

i used for several hours now and my verdict is that its no better or worse than sol

its surprisingly bad at UI which is unexpected

its also lacking in depth vs sol 5.6 which goes above and beyond (which in itself is also an issue at times)

Twice the cost for 4% more intelligence, is it worth it?
I think a more useful metric would be intelligence per dollar spent.
Honestly, who the fuck cares? These leaderboards are meaningless for brand new models. If we were looking at longitudinal data collected over the course of a year or even a quarter or month, this would have some value. Brand new model from established provider shoots to top of charts? This means nothing more than an already famous band briefly topping the charts with their latest song.

It baffles me that intelligent people deploying AI think momentary popularity is a meaningful signal. It's just twitch reactions * FOMO.

I like how Opus 5 doesn't re explain EVERYTHING to me like 4.8 did. GPT 5.6 SOL reasons WAY too hard over nothing, and Opus 5 is an amazing mode. Way to go anthropic
I can't wait for open-source models to compete against this!
The funny thing is that these leaderboards have become completely meaningless for end-users to make decisions on when to use what model.

A single metric ranking is useless because each model has strengths and weaknesses for specific domains and tasks. There is no "one best model" anymore, and you might not even need the best model for the level of complexity for your task.

For e.g. you might use Fable for UI design, Sol for systems design backend work and Kimi K3 for exploit development.

The only purpose these metrics serve is bragging rights for the model companies.

So if you're in Google leadership, you sleep in the office, right? Not merely because you have a ton of work but also because you're deeply ashamed to be seen in public.
Google still has several enormous advantages here:

1. Google Books, Youtube and the Google Search index all provide vast amounts of legally acquired training data.

2. They can easy people into AI using the info box. I think this strategy is working even if it does cannibalize their main revenue source. Better than just withering and leaving all of the money to OpenAI/Anthropic. I would not be surprised if Google has significant layoffs due to reduced ad revenue at some point, but I think they'll still be on top.

3. They already have their hooks into people's lives through Gmail, Google Calendar, Android, etc. The only other companies that come close are Apple (but for a much smaller number of people), and Microsoft (but only for business).

The fact that Google's models might be 20% worse, or a few months behind Anthropic's is completely insignificant in comparison to those things.

"When a measure becomes a target, it ceases to be a good measure"

Goodhart's law.

Anthropic has imo underrated marketing and positioning skills, mythos/fable hype/fear being the most obvious indicator but even the way they almost haphazardly position their models with no intentional cohesion, people see model names and numbers, it's easy to think of them as more intentionally accurate like how cars make S models or AMG, but then the performance and surprises surpass the prior expectation that was set by previous models, rather than having it be more obvious, suddenly the Anthropic Camry will outperform their Corvette without any fanfare.