Can I Run Llama 3.2 Vision on NVIDIA DGX Spark?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 21 lipca 2026

Yes, comfortably — Llama 3.2 Vision 90B at Q4_K_M needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), leaving ~70.2 GB of the NVIDIA DGX Spark's 128 GB, at ~4 tok/s (est.), with room for up to 64K context.

See what else this hardware can run →

Kup ten sprzęt NVIDIA DGX Spark (128GB) — 128 GB VRAM · 150 W board powerUruchom w chmurze NVIDIA A100 80GB w RunPod — od $1.39/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.77/godz. (typical low · varies)

Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

NVIDIA DGX Spark (128GB)
128 GB VRAM · 150 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

NVIDIA DGX Spark Specs

VRAM128 GB
Memory Bandwidth273 GB/s

Llama 3.2 Vision 90B on the NVIDIA DGX Spark: VRAM by quantization

QuantVRAM neededFits 128 GB?Max contextWhole PC
F16181.8 GB✗ No——
Q8_098.5 GB✓ Yes64K—
Q6_K77 GB✓ Yes64K—
Q5_K_M67.1 GB✓ Yes64K—
Q4_K_M57.8 GB✓ Yes64K—
Q3_K_M42 GB✓ Yes64K—
Q2_K33.3 GB✓ Yes64K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 128 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Superseded model. Llama 3.2 Vision has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point. Can I run Llama 4 on NVIDIA DGX Spark? →

Context costs VRAM too. At Q4_K_M on the NVIDIA DGX Spark: 8K 57.8 GB · 32K 67.8 GB · 125K 106.8 GB. Every window this model publishes still fits 128 GB.

No compatible GPU? Llama 3.2 Vision on 8 GB of system RAM, CPU only: runs.

Llama 3.2 Vision Sizes That Fit the NVIDIA DGX Spark (at 8K context)

Llama 3.2 Vision 90BQ4_K_M · 57.8 GB at 8K context · ~4 tok/s (est.)
Llama 3.2 Vision 11BQ4_K_M · 8.5 GB at 8K context · ~31 tok/s (est.)
Buy vs. rent Llama 3.2 Vision
Buy the GPU
~$4,699
NVIDIA DGX Spark · MSRP
Rent by the hour
from $0.77/hr
A100 (80 GB) class

At 2 hrs/day, buying (~$4,699) beats renting at $0.77/hr after about 8.5 years.

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Vast.ai $0.77/hr · typical low · varies
Rent on Vast.ai →
RunPod $1.39/hr
Rent on RunPod →

Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Is the NVIDIA DGX Spark enough to run Llama 3.2 Vision locally?

Yes, comfortably — Llama 3.2 Vision 90B at Q4_K_M needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), leaving ~70.2 GB of the NVIDIA DGX Spark's 128 GB, at ~4 tok/s (est.), with room for up to 64K context.

What's the best Llama 3.2 Vision size for the NVIDIA DGX Spark?

Llama 3.2 Vision 90B at Q4_K_M quantization needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), estimated ~4 tokens/sec, up to 64K context.

Every Llama 3.2 Vision size on the NVIDIA DGX Spark

SizeVRAM at 8KVerdictSpeed
Llama 3.2 Vision 90B57.8 GBRuns~4 tok/s
Llama 3.2 Vision 11B8.5 GBRuns~31 tok/s

Llama 3.2 Vision on Other GPUs

Popular Models on the NVIDIA DGX Spark

VRAM Tier

Troubleshooting

Buying Guide

← Can I Run It? | Llama 3.2 Vision Model Page | NVIDIA DGX Spark GPU Page | VRAM calculator | Check Your Hardware