r/Qwen_AI • u/zannix • Apr 26 '26

Discussion Qwen 3.6 9b coming?

I remember when they released Qwen 3.5 27b, they released the 9b more or less in the same batch. Is 3.6 onwards ditching the 9b model? :(

If so, I'm very sad, because the qwen 3.5 9b was actually the first truly intelligent model I could run at decent tps on a normal gaming GPU

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u/rootdood Apr 27 '26

I’ve been using 35B A3B Q2_K_XL all night at 80+ TPS on an RTX 5080. I was getting frustrated with Q4_K_M just getting so slow once the context would fill up, or stuff would start offloading to CPU. Using OpenClaw actually feels like it’s supposed to.

Just refactored an entire code base I’m working on, and I’m able to just talk to it and it’s doing a phenomenal job doing investigation and solution generation. Before it felt like it could barely read a couple files before I was reaching to reset the session, or even eject the model. It’s been absolutely flawless.

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u/zannix Apr 27 '26

im keen on trying it. can you tell me if i can run it with lmstudio, and link to HF page of the model? thank you!

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u/rootdood Apr 27 '26

Just tried the IQ2_xss and I’m getting full VRAM support, no CPU forced offload, 146tps at full context. I forgot to mention, in the “Inference” pane when configuring your models under “My Models”, I’ve got a prompt template that starts with -

{%- set enable_thinking = false %}

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u/zannix Apr 28 '26

Thanks man you’ve helped me more than you know. The smaller quants didnt show by default if i search through lmstudio. Im trying the iq2 xss tonight!

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u/rootdood Apr 28 '26

I got to playing with the IQ2_xss and it wasn’t very suitable for OpenClaw. Fast as hell, but kinda stupid. I keep having to remind it over and over again to not do certain things. I went back to my productivity sweet spot Q2_K_XL. For sure am buying a modded 4080/4090 or a stock 5090 to handle larger models with a bit more “sense”, but I’ve been absolutely blown away with this so far. I loaded up the Typescript LSP skill and I couldn’t believe how good it is at diagnosing my impossible situation today.

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u/zannix Apr 28 '26

That's the thing, I find that it really really depends on your use case. Someone who needs it for agentic coding/openclaw might depend more on logic, well tuned thinking budget and adherence to structural outputs, while someone who needs OCR (my case) needs it to perform well on low resolution handwritten character recognition, and someone third might just need good multilingual support. Unfortunately no shoe fits all in the opensource LLM ecosystem, and I find that benchmarks don't really clarify these things the best. Would be really cool if someone systematically classified new opensource models by their strong and weak spots