This is a great post that covers a lot of the recent ground. I have a very similar setup after a very similar journey, minus the RTX6000. Worth noting though that a lot of the recent changes make a single 3090/4090 much more viable here too. MTP and the recent improvements to kv quantization in particular, as well as model-specific template & quant fixes. I run a 4090 with the 4-bit quantized variant of the same model now and have had a great experience. Qwen3.5 was already a big step up, but with 3.6 and the rest of the improvements it's substantially more reliable as a daily use tool and I find myself reaching for hosted models a lot less. Feels like I could work entirely without them if they were to disappear without going back to typing every line of code myself.

To make 4-bit fit on one card with reasonable (100k+) context needs a bit more care though. And tuning can be highly specific to your machine, gpu and use-case. But I use a headless server, offload multi-modal to CPU, use fit-target to reduce wasted memory and use q8_0 kv since the 4090 performs well with it... In addition to most of the same config as the author elsewhere. I get 50-60tps generation with a power limit of 275W (450W is default), more than enough to offer a roughly an Opus-speed feedback loop.

I haven't seen many of the issues with looping the author mentions. But I did with Qwen3.5 and in particular other 4-bit quants in the past. But the difference is probably a mix of the improvements above, as well as habits changing to avoid cases where models will loop. For what I'm doing, it seems like I loop Qwen3.6 on the same kind of prompts I'll make Haiku or Sonnet loop on (the latter hide some of their existential loops behind "thinking"). Usually it's cause I was too vague about some aspect of what I'm wanting them to do or I forgot to include some context that smaller models just don't have access to in their smaller knowledge base. But at least for what I'm doing (Rust, React, kubernetes) it's not been a notable problem at all with the latest iteration of this whole stack. And knowledge of standard libraries and default k8s resource kinds has been almost flawless.

There's still plenty of more complex stuff where I'll choose to jump straight to Claude or GLM-5.2, but if it's not worth that jump I've stopped paying for the middle ground as it's usually not much better than just one more iteration through qwen.

All this to say, if you have a 3090/4090, feel free to give the same setup a go. It's come a long way in recent weeks.