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Hardware and Software Compatibility Matrix

This document describes the hardware, software, and platform compatibility for SecAI_OS.

Last updated: 2026-03-08

Base Operating System

Component Value
Base image Fedora Silverblue 42 (uBlue)
Image type Immutable (rpm-ostree)
Builder BlueBuild with cosign signing

GPU Compatibility

Vendor GPU Family Backend LLM Support Diffusion Support Status
NVIDIA RTX 50-series CUDA Yes Yes Supported
NVIDIA RTX 40-series CUDA Yes Yes Supported
NVIDIA RTX 30-series CUDA Yes Yes Supported
AMD RDNA3 ROCm/HIP Yes Yes Supported
AMD RDNA2 ROCm/HIP Yes Yes Supported
AMD CDNA ROCm/HIP Yes Yes Supported
Intel Arc A-series XPU/Vulkan Yes Yes Supported
Intel Arc B-series XPU/Vulkan Yes Yes Supported
Apple M4/M3/M2/M1 Metal/MPS Yes Yes Supported
Any CPU only AVX2/AVX-512/NEON Yes Yes (slow) Supported

Inference Engine

Component Value
LLM inference llama.cpp (llama-server)
Model format GGUF
Multi-GPU Supported (tensor splitting across devices)

Minimum Requirements

Resource Minimum Notes
RAM 16 GB 32 GB recommended for larger models
VRAM 8 GB For GPU-accelerated inference
Storage 64 GB SSD strongly recommended; more needed for multiple models
CPU x86_64 with AVX2 or ARM64 AVX-512 preferred for CPU inference

Recommended Specs by Workload

Workload RAM VRAM Storage Notes
Small LLMs (7B parameters) 16 GB 8 GB 64 GB Runs on most modern hardware
Medium LLMs (13B-30B parameters) 32 GB 16 GB 128 GB RTX 4070+ or equivalent recommended
Large LLMs (65B+ parameters) 64 GB 24 GB+ 256 GB RTX 4090/5080 or multi-GPU setup
Image generation (diffusion) 32 GB 12 GB 128 GB Dedicated VRAM for diffusion models
Multi-model serving 64 GB 24 GB+ 512 GB Multiple models loaded simultaneously

Virtual Machine Support

Platform Format Status Notes
VirtualBox OVA Supported GPU passthrough requires compatible host
VMware (Workstation/ESXi) OVA Supported vGPU or passthrough for GPU acceleration
KVM/QEMU QCOW2 Supported VFIO passthrough for GPU acceleration
Proxmox QCOW2 Supported PCI passthrough for GPU acceleration

VM Notes

  • GPU passthrough is required for GPU-accelerated inference inside a VM.
  • CPU-only inference works in any VM without passthrough.
  • Allocate at least 16 GB RAM to the VM.
  • Nested virtualization is not required.
  • Secure Boot in VM requires the host to support UEFI boot for the guest.