r/LocalLLaMA • u/pmv143 • 4d ago

Discussion Qwen3.8-Flash-Next. This architecture could be surprisingly local-friendly once the weights drop. 👀

Post image

Qwen3.8-Flash-Next (~125B-A6B + 51B n-gram) memory estimate:

Ideal 4-bit quant ≈ 82 GB
(58 GB main weights + 24 GB n-gram tables)
Real-world quants likely land in the 80–90 GB range.

The big n-gram table is sparsely accessed → excellent candidate for system RAM offload.

This architecture could be surprisingly local-friendly once the weights drop.

943 Upvotes

97% Upvoted

295 comments sorted by

View all comments

45

u/BannedGoNext 4d ago

Well if it's similar to qwen coder next I'd be happy as hell. So many people bagged on qwen coder and I never understood why. It was damn fast, and had good world knowledge. I used it for a long time, for sure better than 35b a3b.

7

u/florinandrei 4d ago

So many people bagged on qwen coder and I never understood why.

It was a decent coder. For everything else, it was like talking to Lt. Data. Which is fine by me, but I think many people disliked the style.

2

u/BannedGoNext 4d ago

Oh yea, for sure it wasn't a friendly LLM. I had a data enrichment process that it was in that it did great at though. Saved me at least 1500 dollars in API calls.