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 server · context L 32k
 room      graphics up to 82.8 GB for vLLM (4 x 22.5 GB cards, 0.92 of each)
 runtime   vLLM (from its profile)
 #    Model                   Package                Fit          Speed         Memory    Download
 ───────────────────────────────────────────────────────────────────────────────────────────────────
 1    Qwen3-8B                RedHatAI · AWQ         fits         –             56.7 GB   5.7 GB
 shown     1 of 1 packages
 memory    #1 vLLM on 4 cards: 0.92 of each, runtime 1.50 GB per card (one recording)
 key       Fit is memory only: how many requests of this context the cards hold at once
           ample: twice the requests this ranking assumes or more
           fits: that many, below twice them · tight: at least one, fewer than them
           no fit: not one · the pool is 0.92 of each card vLLM uses, 1.50 GB of it its runtime
           gpu: one card
           gpu_split: 2, 4 or 8 equal cards of the largest size, as the head count allows
           for a fit from size the highest class is fits
           best: the least compression of the same model that fits
           modelroom rates no model family against another
           Speed is measured, see its column.
 Quality of these models for your task: https://artificialanalysis.ai
