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Can RTX 5090 32GB run Llama-3.1-8B-Instruct?

NVIDIA · 32 GB GDDR7 · 1792 GB/s bandwidth · Meta · 8.0B · model ctx up to 128K

Yes — the RTX 5090 32GB (32 GB GDDR7) can run Llama-3.1-8B-Instruct. At Q4 with the default 8K context it needs ≈ 7.0 GB VRAM (weights 4.4 GB + KV cache 1.6 GB + 1 GB runtime overhead), which fits within 32 GB. Decode at Q4/8K: ≈ 214.3 tok/s (measured, batch 1). FP16 (≈ 18.6 GB) also fits, at ≈ 39.2 tok/s (estimated). Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K6.2 GBYes214.3 measured
Q48K default7.0 GBYes214.3 measured
Q432K11.8 GBYes214.3 measured
FP164K17.8 GBYes39.2 est.
FP168K default18.6 GBYes39.2 est.
FP1632K23.4 GBYes39.2 est.

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

QuantWeightsKV cacheOverheadTotal neededRTX 5090 32GB VRAM
Q44.4 GB1.6 GB1 GB7.0 GB32 GB
FP1616.0 GB1.6 GB1 GB18.6 GB32 GB

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