Qwen3.8-27B has been the turning point for me. It's not as strong as the absolute frontier, but it's the first time I feel local coding models are actually functionally useable as daily drivers.
replyMan I am having a hell of a time trying to optimize 3.8 over 3.6. I don’t have a particularly powerful setup but I can usually push 20-30tok/s on 3.6 and I can barely get to 10 on 3.8. Both unsloth same VRAM/RAM distribution more or less. My 3.6 is still producing consistently better results and faster
replyThat's interesting since both models are dense. I wonder if this is more of an optimization issue with 3.8 rather than something inherent to the architecture.
replyCould have sworn I read these were the same architectures the other day .... 3.6 and 3.8 at this size.
replyHave you tried on personal finance analysis? That is what I most want to do but haven’t gotten around to it.
replyI did try some finance analysis earlier this year. I was using a DGX Spark, so I could run some relatively large models, but the results were pretty mixed at the time. I honestly can't remember which models I used anymore.
replyMight be worth trying again now though.
I'm having a really hard time doing on twin DGX spark what I could do on my quad 3090 rig (which is a scaled down version of what I was using before, the power requirements and the noise were really an issue but I loved the speed and the amount of VRAM). The results tend to be inconsistent, there is lots of looping, far more tokens generated for the same job and lower quality output. I suspect there is some kind of regression in the B12X kernels or something to that effect because none of that should happen, the exact same model on both machines gives wildly different results. Probably this will sort itself out over time. If I may ask, what model / software combo were you using?
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