Side-by-side simulation · recommended settings
DGX Spark vs RTX 5090: Which fits your local LLM?
If you need a large model, start with configurations that fit Spark's 128GB memory. If the model fits the 5090's 32GB, compare speed with the same model and input, and include the cost of the PC around the GPU.
Choose devices and a model
Expand comparison settings
Same 117output tokens. Only evidence-qualified acceleration is selected automatically; runtime formats are shown on each device.
Left
ReadyDGX Spark 128GB
Press Start above to generate the same answer on both devices.
Right
ReadyRTX 5090 32GB
Press Start above to generate the same answer on both devices.
With these settings, RTX 5090 32GB finishes the full answer About 8.1× faster.
Compare from input processing to completion of 117 token response.
Which one fits my needs?
Answer completion
RTX 5090 32GB
At the estimate midpoint, it finishes the same answer about 8.1× faster.
Prompt processing
RTX 5090 32GB
The estimated input-processing midpoint is higher at 6,710 tok/s.
Image and video generation
Check the media model
LLM speed does not tell you media-generation performance. Choose the image or video model and resolution separately.
Runtime
Settings for your hardware
llama.cpp · Q4_K_M / Strata 0.1.41 · IQ3_S · MTP-6 · INT8 KV · SSD PLE. When runtime paths differ, the speed gap also includes software and model-format differences.
Estimated power draw
DGX Spark 128GB
Estimated LLM power draw is lower at about 190 W. Noise and physical size need a separate check.
Local pricing
DGX Spark 128GB is the price of finished product, RTX 5090 32GB is the price of GPU separately. For individual GPUs, you need to add the cost of the main body before comparing.
Before choosing hardware
| Measure | DGX Spark 128GB | RTX 5090 32GB |
|---|---|---|
| Available fast memory | 116GB | 30.5GB |
| Memory bandwidth | 273GB/s | 1792GB/s |
| Estimated total time | 9.8 s | 1.2 s |
| Estimated sustained LLM load | about 190W | about 620W |
| Korean price range (KRW) | 952–1,030 × KRW 10,000 | 899–929 × KRW 10,000 |
Estimated ranges for one user. Multi-GPU and multi-device results depend on the runtime and interconnect.