points by jacquesm 4 days ago | 0 comments
Qwen 3.8 and GLM 5.3 are my workhorses right now. Qwen for simpler stuff because it is wicked fast using 'ninfer', GLM 5.3 because it is very good a more complex stuff and less likely to get stuck so I can let it run for much longer without intervention.
[–] dekhn 3 days ago
[–] spwa4 4 days ago
How do you run GLM 5.3?
[–] morgoo 4 days ago
Their parent comment claims they have 8 GPUs and 2 DGX sparks.
[–] spwa4 4 days ago
Even 2 DGX sparks are limited to Q2 at best. As for GPUs, it of course depends, but anything under 50k just can't run it, not even Q2.
And at Q2, I think you're better of with Qwen3-coder-next on one DGX spark (or much better: on any apple silicon max, we are currently in the ridiculous situation that a second hand m1 max 64G will beat a DGX spark that's at least triple the price)
[–] cyanydeez 4 days ago
Halogen flash server for strix halo runs qwen3.8 flash next in 40gb
[–] wjnc 4 days ago
This being /u/jacquesm would imply it is kinder to assume him having that setup than claiming to have that setup.
From a fair bit of coding with the agent, my experience with Qwen 3.8 (Qwen3.8-Flash-Next-GSQ-RCO-IQ3_S-0 on Strata, Qwen 3.8 27B on ninfer). In my particular case, I was trying to clone a recent HN post which allowed you to visualize how out of tune your singing was relative to a song, but as a web app or portable native app.
My experience is that both those models will generate an enormous amount of noise (literally: it was running audible unit tests on my machine to test the note-detection algorithms) while coming to a solution, if they do find a solution- while Claude (whatever the latest model is) or ChatGPT (ditto) will do 1/10th the amount of work to get the right solution. I suspect if I had the resources to run GLM 5.3, it would probably be significantly faster to get to a working solution than Qwen-3.8 27B, but likely still somewhat inferior to Claude or ChatGPT solutions, and also would generate a much larger energy bill on my part.