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Can RTX 4090 24GB run Llama-3.1-8B-Instruct?

NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth · Meta · 8.0B · model ctx up to 128K

Yes — the RTX 4090 24GB (24 GB GDDR6X) 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 24 GB. Decode at Q4/8K: ≈ 85.0 tok/s (measured, batch 1). FP16 (≈ 18.6 GB) also fits, at ≈ 22.0 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 GBYes85.0 measured
Q48K default7.0 GBYes85.0 measured
Q432K11.8 GBYes85.0 measured
FP164K17.8 GBYes22.0 est.
FP168K default18.6 GBYes22.0 est.
FP1632K23.4 GBNo66.3 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 4090 24GB VRAM
Q44.4 GB1.6 GB1 GB7.0 GB24 GB
FP1616.0 GB1.6 GB1 GB18.6 GB24 GB

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