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Can RTX 4090 24GB run Llama-3.2-1B-Instruct?

NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth · Meta · 1.2B · model ctx up to 128K

Yes — the RTX 4090 24GB (24 GB GDDR6X) can run Llama-3.2-1B-Instruct. At Q4 with the default 8K context it needs ≈ 1.9 GB VRAM (weights 0.66 GB + KV cache 0.24 GB + 1 GB runtime overhead), which fits within 24 GB. Decode at Q4/8K: ≈ 534.5 tok/s (estimated, batch 1). FP16 (≈ 3.64 GB) also fits, at ≈ 147.0 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)
Q44K1.78 GBYes534.5 est.
Q48K default1.9 GBYes534.5 est.
Q432K2.62 GBYes534.5 est.
FP164K3.52 GBYes147.0 est.
FP168K default3.64 GBYes147.0 est.
FP1632K4.36 GBYes147.0 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
Q40.66 GB0.24 GB1 GB1.9 GB24 GB
FP162.4 GB0.24 GB1 GB3.64 GB24 GB

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