llmfit/docs/platform-support.md

Platform Support

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Platform support

• Linux -- Full support. GPU detection via nvidia-smi (NVIDIA), rocm-smi (AMD), sysfs/lspci (Intel Arc) and npu-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-smi available.
• Windows -- RAM and CPU detection works. NVIDIA GPU detection via nvidia-smi if 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 --memory=8G recommend --json --limit 10

This is a workaround for recommendation/scoring only; it does not provide true Android GPU runtime detection.

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