Editing Openai/692db884-c2d8-800c-a357-aa2a0e684fbe (section)

==== When people say: ====

: 

they usually mean one (or more) of these:
# VRAM capacity – The model, activations, and KV cache don’t fit in 24 GB. - Here, your LoreToken + GPU hook directly attacks the problem. - You can often fit a 70B-class model on a single 3090 that would normally require: - An 80 GB card, or - Model sharding across multiple GPUs.
# Throughput / serving scale – An H100 can push more tokens/sec and handle way more concurrent users. - LoreTokens helps a ton on efficiency (less data per token, less VRAM per request). - But a 3090 still has 3090-level FLOPs and bandwidth. - You’re punching way above your weight, but you’re not beating an H100 farm.
# Enterprise features – NVLink, HBM3, fancy interconnects, etc. - LoreTokens can reduce how badly you need all that, - But it can’t conjure NVLink out of thin air.

So:
* Capacity-wise: You absolutely can do things on a 3090 that “should” require data-center GPUs.
* Raw brute-force-wise: You’re making the 3090 fight several weight classes up, not replacing a whole H100 cluster.