Qwen3.8 Max now ranked as the best overall model by agentic index

China has caught up is the main takeaway here. The SOTA models are so close that it's really hard to compare them intelligence wise - you have to get a feel for them yourself and what works for you.

What I'm really excited for is the 27B model. 3.6 is still the king of local, and if 3.8 makes the same improvements it could really legitimately make local viable as a default. I'd love to run a perpetual agent on 3.8 that's locally driven.

I clicked through and it showed Qwen at the top at 55.4 compared to 55.3 for Opus Max. I have a screenshot.

Then I clicked away and back, and now it goes Qwen second, with 58.4, to Opus Max at top with 59.2.

I have screenshots of both. The description above the chart is the same in boh cases:

> Artificial Analysis Agentic Index > Represents the weighted average of agentic capabilities benchmarks in the Artificial Analysis Intelligence Index (GDPval-AA v2, ³-Banking)

What happened? How can the scores change so much in a few seconds?

I believe it. It's extremely good at troubleshooting. I gave Qwen and Kimi K3 the same annoying, complicated, intermittent bug to track down. Kimi did a bit better in understanding the existing code, but Qwen built some diagnostic tools and did an excellent statistical analysis on the log data. Qwen got way closer to the truth.

I'm very much looking forward to their forthcoming smaller model Qwen 3.8 releases. A version that can easily run locally would be great.

Opus is still first in Intelligence Index followed by Fable, GPT 5.6, Kimi K3 then Qwen 3.8 max. https://artificialanalysis.ai/#intelligence

Our leaderboard combines Arena ELO, AA Intelligence index, latency and speed and goes: #1 Opus 5 #2 Kimi K3 #3 Qwen3.8 Max #4 GPT 5.6 Sol

Source: http://pellmell.ai/leaderboard.

This jumps around a lot based on the top throughput and latency of whatever provider happens to be best at the moment.

Any benchmark showing Opus 5 as the best just loses credibility for me. Anyone who's actually used Opus 5 daily knows what I'm talking about.

Strange that the page https://artificialanalysis.ai/agents/coding-agents doesn't even mention "Qwen" once if it's now the "best" according to one of their one index?

Anthropic is a bit nuts, I had $260 of credits on my max account for the extra usage the other night. It was expiring, so I figured I'll fire up an agentic swarm to deep dive and make some deep changes to some old cold bases.. literally 25 minutes or less, $260 burnt, it didn't get get into the implementation, just wrote a ton of useless plans for the most part. It really opened my eyes to what they expect to charge people.. wayyyy overpriced.

The fact that the Chinese models have caught up on benchmarks suggests to me that its likely we will start to transition now into much more of a brand war. It will be subjective qualities that drive our decisions more than measures of absolute intelligence. Already I am choosing models more because I like the personality or style of what they do than because I think they have the absolute highest chance of outputting the most technically correct answer to any given prompt. It will be very interesting to see how things evolve in this direction.

Hopefully this boils down to the smaller versions they've teased. In my experience, Qwen models are the closest to the "less knowledge, more intelligence" (yes, the two are hugely correlated!) ideal some tool-dependent tasks need. Even the 3.5 2B can be easily prompted to always lean on tools and not jump to false conclusions (although its actual coding skills are abysmal, as you'd expect).

I am so excited for Qwen 3.8 27B. It’s a shame how slow prefill (~3-400) is on a strix halo but it’s such a good model for agentic tasks.

I find that surprising.

I've been trying it on several projects and have found it's pretty sloppy. It leaves stuff broken, doesn't reliably write tests to check its own work unless explicitly prompted, misunderstands the assignment, etc.

It is smart and reasonably quick but not reliable.

Why does an open weights model cost nearly the same as GPT5.6? $1.14 vs $1.23 on the cost index. Since you can't presumably run this on your own hardware given the model size and hence gain other things like privacy, I don't see any reason to move away from GPT at this rate.

A couple days ago they had published an overall score of 53 for this model, but that was removed and today it returned with a score of 56.

I wasn't able to find an explanation from them. Anyone knows what happened?

I distrust any benchmark where Opus 5 beats Fable 5.

Is there a path to distill this model to do very specific things? Like a RAG strategy for a small (or even large) corpus?

Haven't tried this yet, but going to soon! I have to wonder what happened at Anthropic. We've cancelled our subscription in favor of OpenCode & Codex. Sol is just so good & OC goes so far for every $ spent. Claude's become a pain to work with - average output with an annoying personality. Who knew this would be an issue even a year ago? In any case, loving the stuff from the Chinese models!

I just don't think you can combine speed, latency, price and intelligence into a single useful metric.

Clearly the weighting of those things depends on the usecase

Anthropic have a real fight on their hands now. The competition is no longer 6 months behind, it's 6 days. If this had come out two or three weeks earlier this would be an absolute market leader on both quality and timeline.

This has me hopeful for Qwen3.8-27B!

I'm seeing opus 59.2, Qwen 58.4?

Qwen is just crushing it overall. I regularly use 3.7-flash for everyday coding needs and it gets the job done.

Out of curiosity, what's currently the best model I can use locally?

That took what 2 years? I love how the chip ban made them more efficient

curious about methodology. ive seen them post results for claude/codex when they only ran over benchmarks 3 times per model...

Could someone like Apple be playing the long game - Good Enough(tm) intelligence will eventually fit in our pocket and homes?

Qwen is the way to go

It is also the most expensive open source frontier model, per task; cf. Cost per Intelligence Index Task. If it is as good as the benchmarks indicate -- I'll never know because I see no reason to try it -- it is a positive indicator for Qwen and China.

Well, that's the bad index then. It is barely usable in my opinion compared to other Chinese frontier models.

Does it matter, it's all non deterministic bs ware and deepseek is eating the Americans lunch

It doesn’t even show up in the raw intelligence index, so how could it possibly be the best?

Go China!

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