| 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 the model with lms load {model-name} |
lms command not found | PATH issue after a successful install | Refresh your shell by running source ~/.bashrc (or the shell init file suggested by the installer) |
| Model load fails — CUDA out of memory | Model too large for available memory | Switch to a smaller model or a different quantization |
| LM Link: devices not connecting or remote models not visible | Devices not in the same Link, or LM Link not set up on both | Ensure the hardware platform 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
Some hardware platforms use Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. If you hit memory pressure even when within rated capacity, manually flush the buffer cache with:
sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches'
For latest known issues, see the documentation linked under Resources for your hardware platform.