Can Llama 3.2 3B Instruct run on NVIDIA RTX 4000 20 GB?

Yes. Calculated memory fit: Llama 3.2 3B Instruct can run entirely in this GPU’s usable VRAM at one or more supported quantizations.

Can it run?

Can it run?: Yes, full GPU fit (calculated estimate).
Full GPU fit?: Yes
Model: Llama 3.2 3B Instruct · 3.2B
GPU: NVIDIA RTX 4000 20 GB · 20 GB advertised

Memory calculation

Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.

Model weights	1.9 GB
KV cache	0.9 GB
Runtime reserve	0.6 GB
Safety margin	0.3 GB
Required (estimated)	3.7 GB
GPU usable VRAM	18.0 GB

Result: FITS IN VRAM

Quantization table

Quantization	2K	4K	8K	16K	32K	64K	128K
BF16	Fits	Fits	Fits	Fits	Fits	Fits	Limited context
FP16	Fits	Fits	Fits	Fits	Fits	Fits	Limited context
Q3	Fits	Fits	Fits	Fits	Fits	Fits	Fits
Q4	Fits	Fits	Fits	Fits	Fits	Fits	Fits
Q5	Fits	Fits	Fits	Fits	Fits	Fits	Fits
Q6	Fits	Fits	Fits	Fits	Fits	Fits	Fits
Q8	Fits	Fits	Fits	Fits	Fits	Fits	Limited context

What fits entirely in VRAM?

BF16 at 16K context
BF16 at 2K context
BF16 at 32K context
BF16 at 4K context
BF16 at 64K context
BF16 at 8K context
FP16 at 16K context
FP16 at 2K context
FP16 at 32K context
FP16 at 4K context
FP16 at 64K context
FP16 at 8K context

What requires RAM offload?

Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.

Available graphics cards

These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.

Check price on Amazon

HP NVIDIA RTX 4000 Ada 20 GB 4DP Graphics

20 GB · Amazon EXACT

$3501.00

Check price on Amazon

Lenovo

Lenovo NVIDIA RTX 4000 Ada 20 GB GDDR6

20 GB · Amazon unmatched

Check availability

Sources

Model: official config meta-llama/Llama-3.2-3B-Instruct (official-fallback-config). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: FITS_IN_VRAM. Amazon: affiliate commerce match, not a spec source.