> ## 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.

# Platform Support

> Supported platforms, GPU vendors, and backend detection methods

llmfit supports Linux, macOS, and Windows with automatic GPU detection across NVIDIA, AMD, Intel, Apple Silicon, and Ascend NPU hardware.

## Support Matrix

| Platform                  | RAM/CPU Detection | GPU Detection                        | Status         |
| ------------------------- | ----------------- | ------------------------------------ | -------------- |
| **Linux**                 | Full              | NVIDIA, AMD, Intel Arc, Ascend NPU   | ✓ Full support |
| **macOS (Apple Silicon)** | Full              | Unified memory via Metal             | ✓ Full support |
| **macOS (Intel)**         | Full              | Discrete GPU if nvidia-smi available | ✓ Supported    |
| **Windows**               | Full              | NVIDIA GPU via nvidia-smi            | ✓ Supported    |

## GPU Vendor Support

llmfit detects GPUs from multiple vendors and automatically identifies the optimal inference backend:

| Vendor                     | Detection Method                     | VRAM Reporting                | Backend       |
| -------------------------- | ------------------------------------ | ----------------------------- | ------------- |
| **NVIDIA**                 | `nvidia-smi`, sysfs fallback         | Exact dedicated VRAM          | CUDA          |
| **AMD**                    | `rocm-smi`, sysfs fallback           | Exact or estimated            | ROCm / Vulkan |
| **Intel Arc (discrete)**   | sysfs `mem_info_vram_total`          | Exact dedicated VRAM          | SYCL (oneAPI) |
| **Intel Arc (integrated)** | `lspci`                              | Shared system memory          | SYCL (oneAPI) |
| **Apple Silicon**          | `system_profiler SPDisplaysDataType` | Unified memory (= system RAM) | Metal         |
| **Ascend NPU**             | `npu-smi info`                       | HBM capacity from npu-smi     | NPU (Ascend)  |

### Multi-GPU Support

llmfit supports multi-GPU setups for same-model configurations (e.g., 2x RTX 4090):

* **NVIDIA**: Multi-GPU detection via `nvidia-smi` aggregates VRAM across all cards
* **AMD**: Per-GPU VRAM via `rocm-smi --showmeminfo vram`
* **Ascend**: Multiple NPUs detected via `npu-smi info -l`

For multi-GPU inference backends (llama.cpp, vLLM), models can be split across cards, so total VRAM is used for fit scoring.

## Backend Detection

llmfit automatically identifies the acceleration backend for accurate speed estimation:

### GPU Backends

* **CUDA**: NVIDIA GPUs detected via nvidia-smi or sysfs `/sys/class/drm` with vendor ID `0x10de`
* **ROCm**: AMD GPUs with ROCm installed (detected via `rocm-smi`)
* **Vulkan**: AMD GPUs without ROCm (Windows, Linux without ROCm)
* **SYCL**: Intel Arc GPUs (discrete and integrated)
* **Metal**: Apple Silicon unified memory GPUs
* **Ascend**: Huawei Ascend NPUs via `npu-smi`

### CPU Fallback

* **CPU (ARM)**: ARM architecture or Apple CPUs (no GPU detected)
* **CPU (x86)**: x86 architecture (no GPU detected)

## Unified Memory Platforms

Some platforms use unified memory architectures where GPU and CPU share the same RAM pool:

### Apple Silicon

All Apple Silicon Macs (M1, M2, M3, M4 series) use unified memory:

* VRAM = total system RAM (shared pool)
* Detection: `system_profiler SPDisplaysDataType` checks for "Apple M" chipset
* No separate CPU offload path (GPU and CPU use the same memory)

### AMD Unified Memory APUs

Ryzen AI series APUs share system RAM between CPU and GPU:

* **Ryzen AI MAX/MAX+** (Strix Halo): up to 128 GB unified
* **Ryzen AI 9/7/5** (Strix Point, Krackan Point): configurable shared memory via BIOS

Detection: CPU name contains "Ryzen AI" → GPU VRAM set to system RAM

### NVIDIA Grace/DGX Spark

NVIDIA Grace Blackwell unified memory SoCs (GB10, GB20):

* Detection: `nvidia-smi --query-gpu=addressing_mode` returns "ATS" (Address Translation Services)
* VRAM fallback: `/proc/meminfo` total RAM when nvidia-smi reports 0
* System RAM used as unified memory pool

## VRAM Estimation Fallback

When GPU tools fail to report VRAM (broken nvidia-smi, VMs, passthrough setups), llmfit estimates VRAM from the GPU model name.

Supported models include:

* NVIDIA: RTX 50/40/30/20 series, GTX 16 series, datacenter (H100, H200, A100, L40, T4)
* AMD: RX 9000/7000/6000/5000 series, Radeon 800M/8000 series, Instinct MI300X/MI250X
* Fallback: Generic RTX → 8 GB, GTX → 4 GB

### Manual Override

If autodetection fails or reports incorrect values, use `--memory` to override:

```bash theme={null}
llmfit --memory=32G
llmfit --memory=24GB system
llmfit --memory=16000M fit --perfect
```

Accepted suffixes: `G`/`GB`/`GiB` (gigabytes), `M`/`MB`/`MiB` (megabytes), `T`/`TB`/`TiB` (terabytes). Case-insensitive.

## Platform-Specific Notes

* **WSL (Windows Subsystem for Linux)**: Detected via `WSL_INTEROP` / `WSL_DISTRO_NAME` environment variables or `/proc/version` containing "microsoft"
* **Containers (Toolbx, Docker)**: Sysfs fallback detects GPUs when nvidia-smi is unavailable
* **Flatpak**: `flatpak-spawn --host lspci` used to query GPU info from host system
* **macOS (newer versions)**: Available RAM fallback via `vm_stat` when sysinfo reports 0

## Next Steps

* [Linux Platform Guide](/platforms/linux)
* [macOS Platform Guide](/platforms/macos)
* [Windows Platform Guide](/platforms/windows)