NVIDIA DGX Spark — Local LLM Performance & Compatibility

Compact AI development desktop built around the GB10 Grace Blackwell Superchip — a 20-core Grace ARM CPU plus a Blackwell GPU (6,144 CUDA cores) sharing 128 GB of unified LPDDR5x memory at 273 GB/s. Runs the full CUDA stack, unlike Apple Silicon, making it ideal for fine-tuning and inference of 70B-class models. Launched at $3,999 in October 2025; price raised to $4,699 in February 2026 due to memory supply constraints.

Technical Specifications

VRAM128 GB
Memory Bandwidth273 GB/s
TDP150 W
ArchitectureGB10 Grace Blackwell Superchip
Release Year2025
MSRP at Launch$4,699
Inference Speed (Llama 3.1 8B Q4_K_M)~60 tokens/sec
Inference Speed (Llama 3.3 70B Q4_K_M)~20 tokens/sec

LLMs Compatible with 128 GB VRAM

All models below run comfortably in 128 GB VRAM with Q4_K_M quantization.

Llama 3.324 GB VRAM · Q2_K_XS (Tight) · ollama run llama3.3
Llama 3.1 Family6 GB VRAM · Q4_K_M · ollama run llama3.1
Llama 424 GB VRAM · Q4_K_M · ollama run llama4:maverick
DeepSeek R120 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b
Qwen 380 GB VRAM · Q4_K_M · ollama run qwen3:235b-a22b
Qwen3-Coder8 GB VRAM · Q4_K_M · ollama run qwen3-coder:80b-a3b-q4
Gemma 316 GB VRAM · Q4_K_M · ollama run gemma3:27b
Mistral Small 3.114 GB VRAM · Q4_K_M · ollama run mistral-small3.1

Best Use Cases

Quick Start with Ollama

Install Ollama then run the recommended model for this GPU:

ollama run llama3.3:70b

FAQ

Can the NVIDIA DGX Spark run local LLMs?

Yes — the NVIDIA DGX Spark has 128 GB VRAM and runs Compact AI development desktop built around the GB10 Grace Blackwell Superchip — a 20-core Grace ARM CPU plus a Blackwel

How fast is the NVIDIA DGX Spark for AI inference?

The NVIDIA DGX Spark runs Llama 3.1 8B at ~60 tokens/sec with Q4_K_M quantization. For the 70B model it achieves ~20 tokens/sec.

What LLMs can I run on 128 GB VRAM?

With 128 GB you can run: Llama 3.3, Llama 3.1 Family, Llama 4, DeepSeek R1, Qwen 3. Use Ollama for the easiest setup: ollama run llama3.3:70b.

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