> ## Documentation Index > Fetch the complete documentation index at: https://mintlify.com/AlexsJones/llmfit/llms.txt > Use this file to discover all available pages before exploring further. # Windows Platform Support > NVIDIA GPU detection, Scoop installation, and WSL considerations for Windows Windows supports RAM/CPU detection and NVIDIA GPU detection via nvidia-smi. ## GPU Detection ### NVIDIA GPUs llmfit detects NVIDIA GPUs via two methods: #### 1. nvidia-smi (Primary) ```powershell theme={null} nvidia-smi --query-gpu=memory.total,name --format=csv,noheader,nounits ``` **Requirements:** * NVIDIA drivers installed * nvidia-smi.exe in PATH (usually `C:\Program Files\NVIDIA Corporation\NVSMI\`) **Multi-GPU Support:** * Aggregates same-model GPUs (e.g., 2x RTX 4090 → count=2, per-card VRAM=24GB) * Total VRAM = per-card VRAM × count #### 2. WMI (Windows Management Instrumentation) Fallback method when nvidia-smi is unavailable or for non-NVIDIA GPUs: ```powershell theme={null} # PowerShell (primary) Get-CimInstance Win32_VideoController | Select-Object Name,AdapterRAM # wmic (legacy fallback) wmic path win32_VideoController get Name,AdapterRAM /format:csv ``` **Detected GPUs:** * NVIDIA (GeForce, RTX, Quadro, Tesla) → CUDA backend * AMD (Radeon, RX) → Vulkan backend * Intel (Arc, Iris) → SYCL backend **Filtered entries:** * Microsoft Basic Display Adapter * Virtual/Remote display adapters **VRAM Limitations:** WMI `AdapterRAM` is a 32-bit field capped at \~4 GB. For GPUs with >4 GB VRAM, llmfit estimates from GPU name: ```rust theme={null} if vram_gb < 0.1 || (vram_gb <= 4.1 && estimate_vram_from_name(name) > 4.1) { vram_gb = estimate_vram_from_name(name); } ``` ## Installation Methods ### Scoop (Recommended) ```powershell theme={null} scoop install llmfit ``` **If Scoop is not installed:** ```powershell theme={null} # Install Scoop Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser Invoke-RestMethod -Uri https://get.scoop.sh | Invoke-Expression # Install llmfit scoop install llmfit ``` ### From Source **Prerequisites:** * Rust toolchain: [https://rustup.rs/](https://rustup.rs/) * Git for Windows: [https://git-scm.com/download/win](https://git-scm.com/download/win) ```powershell theme={null} git clone https://github.com/AlexsJones/llmfit.git cd llmfit cargo build --release # Copy binary to PATH copy target\release\llmfit.exe C:\Windows\System32\ # or add target\release to PATH ``` ### Binary Download Download the latest Windows binary from [GitHub Releases](https://github.com/AlexsJones/llmfit/releases): 1. Download `llmfit-windows-x64.zip` 2. Extract `llmfit.exe` 3. Move to a directory in PATH (e.g., `C:\Program Files\llmfit\`) 4. Add to PATH via System Properties → Environment Variables ## WSL (Windows Subsystem for Linux) llmfit can run natively on Windows or inside WSL. Each has trade-offs: ### Running in WSL2 **Advantages:** * Native Linux environment * Better support for ROCm (AMD) if needed * Consistent with Linux instructions **Requirements:** * WSL2 (not WSL1) * NVIDIA CUDA drivers for WSL: [https://docs.nvidia.com/cuda/wsl-user-guide/](https://docs.nvidia.com/cuda/wsl-user-guide/) **Installation:** ```bash theme={null} # Inside WSL2 curl -fsSL https://llmfit.axjns.dev/install.sh | sh ``` **GPU Detection in WSL:** llmfit detects WSL via: ```bash theme={null} echo $WSL_DISTRO_NAME cat /proc/version | grep -i microsoft ``` NVIDIA GPUs work via nvidia-smi in WSL2: ```bash theme={null} nvidia-smi # Should show GPU if CUDA drivers are installed ``` **Known Limitations:** * AMD ROCm not officially supported in WSL * Intel Arc support limited in WSL ### Running Natively on Windows **Advantages:** * Direct GPU access (no virtualization overhead) * Better NVIDIA GPU support * WMI fallback for non-NVIDIA GPUs **Recommendation:** Use native Windows installation for best GPU detection. ## Troubleshooting ### GPU Not Detected #### NVIDIA GPU 1. Check if nvidia-smi works: ```powershell theme={null} nvidia-smi ``` 2. If nvidia-smi not found: ```powershell theme={null} # Check PATH $env:PATH -split ';' | Select-String -Pattern 'NVIDIA' # Add to PATH if missing $env:PATH += ";C:\Program Files\NVIDIA Corporation\NVSMI" ``` 3. Reinstall NVIDIA drivers: * Download from [https://www.nvidia.com/Download/index.aspx](https://www.nvidia.com/Download/index.aspx) * Use "Clean Install" option 4. Check WMI fallback: ```powershell theme={null} Get-CimInstance Win32_VideoController | Select-Object Name,AdapterRAM ``` 5. Manual override: ```powershell theme={null} llmfit --memory=24G system ``` #### AMD/Intel GPU AMD and Intel GPUs rely on WMI detection: ```powershell theme={null} Get-CimInstance Win32_VideoController | Select-Object Name,AdapterRAM,DriverVersion ``` **Expected output:** ``` Name AdapterRAM DriverVersion ---- ---------- ------------- AMD Radeon RX 7900 XTX 25769803776 31.0.24001.18012 ``` If AdapterRAM shows low value (\< 4 GB) for high-VRAM GPU, llmfit estimates from name. ### VRAM Shows Incorrect Value **WMI 32-bit limitation:** WMI reports wrong VRAM for GPUs with >4 GB: ```powershell theme={null} # Check raw value (Get-CimInstance Win32_VideoController).AdapterRAM ``` llmfit automatically falls back to name-based estimation. If incorrect, use manual override: ```powershell theme={null} llmfit --memory=16G ``` ### nvidia-smi Works But llmfit Doesn't Detect GPU **PATH issue:** ```powershell theme={null} # Check if nvidia-smi is in PATH Get-Command nvidia-smi # If not found, add to PATH $env:PATH += ";C:\Program Files\NVIDIA Corporation\NVSMI" # Make permanent via System Properties → Environment Variables ``` **Command execution issue:** llmfit spawns `nvidia-smi` as a subprocess. Check for permission issues: ```powershell theme={null} # Run llmfit as Administrator Start-Process powershell -Verb RunAs llmfit system ``` ### WSL-Specific Issues **nvidia-smi not working in WSL:** 1. Install CUDA drivers for WSL: * Download from [https://developer.nvidia.com/cuda-downloads?target\_os=Linux\&target\_arch=x86\_64\&Distribution=WSL-Ubuntu](https://developer.nvidia.com/cuda-downloads?target_os=Linux\&target_arch=x86_64\&Distribution=WSL-Ubuntu) * Follow WSL-specific installation steps 2. Restart WSL: ```powershell theme={null} wsl --shutdown wsl ``` 3. Verify GPU access: ```bash theme={null} nvidia-smi ``` **WSL not detected:** llmfit checks for WSL via environment variables: ```bash theme={null} echo $WSL_DISTRO_NAME echo $WSL_INTEROP cat /proc/version | grep -i microsoft ``` If none exist, WSL detection fails (non-critical, only affects logging). ### Performance Issues **High VRAM usage:** Check VRAM usage via Task Manager: 1. Task Manager → Performance → GPU 2. Watch "Dedicated GPU memory" usage If near capacity: * Close GPU-intensive apps (browsers, games) * Use `--max-context` to limit context length: ```powershell theme={null} llmfit --max-context 4096 ``` **Slow inference estimates:** llmfit uses GPU memory bandwidth for speed estimation. Check GPU model detection: ```powershell theme={null} llmfit system # GPU: NVIDIA GeForce RTX 4090 (24.00 GB VRAM, CUDA) ``` If GPU model is wrong or generic ("NVIDIA GPU"), speed estimates may be inaccurate. ## Known Limitations ### AMD GPU Support * **No ROCm on Windows**: AMD GPUs use Vulkan backend (slower than ROCm on Linux) * **VRAM detection**: Relies on WMI (may be inaccurate for >4 GB GPUs) * **Workaround**: Use manual override for accurate VRAM: ```powershell theme={null} llmfit --memory=24G # For RX 7900 XTX ``` ### Intel Arc Support * **Limited detection**: Relies on WMI * **SYCL backend**: Requires Intel oneAPI runtime (not auto-detected) * **Recommendation**: Use NVIDIA GPU or run in WSL2 for better Intel Arc support ### Multi-GPU Limitations * **Different vendors**: llmfit uses the GPU with most VRAM as primary * **Mixed NVIDIA + AMD**: Only NVIDIA detected via nvidia-smi, AMD via WMI * **Check detection**: ```powershell theme={null} llmfit system # Should list all detected GPUs ``` ## Next Steps * [Platform Overview](/platforms/overview) * [Linux Platform Guide](/platforms/linux) * [macOS Platform Guide](/platforms/macos)