Are models with N-Gram tables going to completely change the AI race?
Heat trend
The percentage is based on available heat signal, not comment count or independent people.
Qwen model activity is surfacing — worth tracking for capability changes, ecosystem impact, and availability.
The introduction of n-gram tables, as seen with Qwen 3.8 Flash Next, could potentially revolutionize AI model deployment.…
The news about Qwen 3.8 Flash Next is the first I'm reading about n-gram tables. I may be completely misunderstanding how they work but it seems they could open the door for 1T+ parameter models to be run on a single server with modest GPUs and a ton of system RAM rather than needing a rack of GPU servers connected with something like NVlink.
Could we be looking at shrinking the capability gap between self hosted and flagship models faster than we thought, or am I way off base?