NVIDIA DGX Spark vs M2 Pro 16GB for local LLMs
91 reports on the NVIDIA DGX Spark and 3 on the M2 Pro 16GB
Which is faster for local LLMs?
Nobody has reported the same model at the same quant on both cards yet, so there's no measured head-to-head. Memory bandwidth, which caps how fast a card can write, is 33% higher on the NVIDIA DGX Spark (273 GB/s on the NVIDIA DGX Spark, 205 on the M2 Pro 16GB). The estimates below compare them on the models people run most.
NVIDIA DGX Spark
- Memory
- 128GB unified
- Memory bandwidth
- 273 GB/s
- FP16 compute
- 125 TFLOPS
- Reports
- 91
M2 Pro 16GB
- Memory
- 16GB unified
- Memory bandwidth
- 205 GB/s
- FP16 compute
- 6.8 TFLOPS
- Reports
- 3
Estimated by the calculator
The quant the calculator recommends for each card and its estimated speed at a 32,768-token context with 32 GB of system RAM, from memory bandwidth and the model's shape.
| Model | NVIDIA DGX Spark | M2 Pro 16GB |
|---|---|---|
| Qwen3.8 27B | 4.0 t/sFP16 | doesn't fit at these settings |
| Qwen3.8 125B · 6B active | 14.4 t/sQ6_K | doesn't fit at these settings |
| Qwen3.6 35B · 3B active | 14.5 t/sFP16 | doesn't fit at these settings |
| DeepSeek V4 Flash 284B · 13B active | 38.3 t/sQ2_K | doesn't fit at these settings |
| Qwen3.6 27B | 4.0 t/sFP16 | doesn't fit at these settings |
| Gemma 4 26B · 4B active | 10.8 t/sFP16 | doesn't fit at these settings |
Change the context, RAM or model in the calculator: NVIDIA DGX Spark · M2 Pro 16GB
Every report on each card, with its source: NVIDIA DGX Spark · M2 Pro 16GB