| Symptom | Cause | Fix |
|---|---|---|
| API returns "model not found" error | Model not downloaded or loaded in LM Studio | Run lms ls to verify download status, then load model with lms load {model-name} |
lms command not found | PATH issue assuming successful installation | Refresh your shell by running source ~/.bashrc |
| Model load fails - CUDA out of memory | Model too large for available VRAM | Switch to a smaller model or a different quantization |
| LM Link: devices not connecting or remote models not visible | Devices not in same Link, or LM Link not set up on both | Ensure both Spark and laptop are signed in and joined to the same Link at lmstudio.ai/link. Restart LM Studio/llmster after joining. See LM Link for how it works. |
NOTE
DGX Spark uses a Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. With many applications still updating to take advantage of UMA, you may encounter memory issues even when within the memory capacity of DGX Spark. If that happens, manually flush the buffer cache with:
sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches'
For the latest known issues, please review the DGX Spark User Guide.