Qwen3.8/Qwen3.6 has a weird self doubt/thinking too much problem. You can prompt it away. I would say it "approximates" Opus 4.X class models well enough especially for coding/linux problems.

The only reason I stopped using it as much is I was getting 25-35tok/s on Intel B70 (non-quant) which made some responses slow. For a long running/autonomous task, it would probably be sufficient.

There is the rule of thumb that if you take the geometric mean of the total and active parameters of an MoE model you get the equivalent size of an equally capable dense model.

If you follow that formula, you would expect a 125b-a6b model to match a 27b model (sqrt(125*6) = 27.3). That does not feel like a coincidence

Thanks. My current stack ranking of anthropic models is:

4.6 ~= 4.8

4.7 much worse.

Fable and newer consistently tells me to pound sand, so I’m not sure what I’m paying $200/month for. 4.8 sometimes does too, but it’s at least usable most of the time.

So, I’d expect this to mostly replace Claude for my workflows. The main tradeoff for me should mostly be token throughput vs. no longer really trusting anthropic.

I've got the A10B hooked up to deer-flow and it does remarkable well when you dont need to baby sit it.