They didn't run all benchmarks. It's the best in AA agentic index (GDPval-AA v2, ³-Banking) but not coding index (DeepSWE which is missing, Terminal-Bench v2.1 they have 81% vs 90% for Sol, SWE-Atlas-QnA missing).

According to those graphs, Grok 4.5 appears to be the most cost-effective model.

Does "artificial analysis" mean what it says? Dubious.

But: I've been very impressed by the larger Qwen Models, and a brief try of Kimi also impressed me.

A lingering sense of quality degradation when going deep remains.

But that's not an accusation: they seem to be hitting the compute/quality tradeoff extremely well.

And on-prem capability is simply irreplaceable.

Apart from all the innovations that were driven by the strive for this optimization: quantization, "distilling" (without obvious mad-cows-disease)... I think China was an invaluable player in this progress. Intuitively, I'd even go so far to speculate that LLaMa wouldn't exist without the competition.

Different benchmarks:

> Artificial Analysis Agentic Index: Represents the weighted average of agentic capabilities benchmarks in the Artificial Analysis Intelligence Index (GDPval-AA v2, Tau³-Banking)

> Artificial Analysis Coding Agent Index v1.3 incorporates 3 benchmarks: DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA

Qwen3.8 Max is 55.4 on the Agentic Index but hasn't been tested for the Coding Agent Index.

Indeed, and this Qwen 3.8 max specific page:

https://artificialanalysis.ai/models/qwen3-8-max

Doesn't have the claim either. Clickbait?