wehub-resource-sync
2.3 KiB
2.3 KiB
Platform Support
Platform support
- Linux -- Full support. GPU detection via
nvidia-smi(NVIDIA),rocm-smi(AMD), sysfs/lspci(Intel Arc) andnpu-smi(Ascend). - macOS (Apple Silicon) -- Full support. Detects unified memory via
system_profiler. VRAM = system RAM (shared pool). Models run via Metal GPU acceleration. - macOS (Intel) -- RAM and CPU detection works. Discrete GPU detection if
nvidia-smiavailable. - Windows -- RAM and CPU detection works. NVIDIA GPU detection via
nvidia-smiif installed. - Android / Termux / PRoot -- CPU and RAM detection usually work, but GPU autodetection is not currently supported. Mobile GPUs such as Adreno typically are not visible through the desktop/server probing interfaces llmfit uses.
GPU support
| Vendor | Detection method | VRAM reporting |
|---|---|---|
| NVIDIA | nvidia-smi |
Exact dedicated VRAM |
| AMD | rocm-smi |
Detected (VRAM may be unknown) |
| Intel Arc (discrete) | sysfs (mem_info_vram_total) |
Exact dedicated VRAM |
| Intel Arc (integrated) | lspci |
Shared system memory |
| Apple Silicon | system_profiler |
Unified memory (= system RAM) |
| Ascend | npu-smi |
Detected (VRAM may be unknown) |
If autodetection fails or reports incorrect values, use --memory, --ram, or --cpu-cores to override (see Hardware overrides).
Android / Termux note
On Android setups such as Termux + PRoot, llmfit usually cannot see mobile GPUs through the standard Linux detection paths (nvidia-smi, rocm-smi, DRM/sysfs, lspci, etc.). In those environments, "no GPU detected" is expected with the current implementation.
If you still want GPU-style recommendations on a unified-memory phone or tablet, use a manual memory override:
llmfit --memory=8G fit -n 20
llmfit recommend --json --memory=8G --limit 10
This is a workaround for recommendation/scoring only; it does not provide true Android GPU runtime detection.