Know what AI your PC can actually run.
Set or scan your hardware once. AIPCFit checks local AI compatibility for Ollama, LM Studio, ComfyUI, and PyTorch, recommends fitting models and workflows, explains bottlenecks, and tells you when an upgrade is actually worth considering.
Deterministic
Rules and structured data, not AI guessing.
Private by default
Your PC profile stays in your browser.
Source-backed
Official sources and verification dates are visible.
How it works
From hardware to a useful answer.
Set or scan your PC
Select your hardware manually or paste the result from the read-only Windows scanner.
Check real workload fit
Ollama and LM Studio models, ComfyUI workflows, and PyTorch CUDA hardware paths are checked against verified compatibility data.
Get a practical next step
See what to run, the likely bottleneck, and whether upgrading GPU memory or RAM would actually help.
Your PC
Start with your hardware.
Your selections are reused across Ollama, LM Studio, ComfyUI, PyTorch, workload recommendations, and upgrade advice.
My PC
Set your hardware once
Your hardware profile is stored only in this browser and reused across compatibility tools.
Your PC
Check an Ollama model
Choose your GPU, system memory, and model. The result combines verified Ollama compatibility with a conservative VRAM planning estimate.
Using My PC
NVIDIA GeForce RTX 5080 16GB
32 GB system RAM
Compatibility result
Good GPU fit
The selected GPU appears to have useful VRAM headroom for this model.
GPU VRAM
16 GB
Model file
5.2 GB
Planning VRAM
~6.7 GB
Context notes
- This is a relatively modest context setting.
- Longer contexts generally require more memory.
What this means
- The GPU has enough VRAM for the model weights plus the conservative planning headroom used by this tool.
- Actual VRAM usage still depends on context length, runtime settings, and concurrent GPU workloads.
- This is an estimate and not a vendor guarantee.
Learn before you upgrade
Understand what your hardware actually needs.
Evidence & trust
Recommendations you can inspect.
Compatibility facts come from structured source data. Planning heuristics are kept separate from official hardware requirements.
No benchmark speed, tokens per second, or exact generation-time claims are invented.
NVIDIA
NVIDIA GPU specifications
GPU model, architecture, memory type, and VRAM catalog data.
Last verified: 2026-09-25
Ollama
Ollama Windows compatibility
Used to verify the Windows NVIDIA acceleration path.
Last verified: 2026-09-25
Ollama
Ollama model catalog
Model file size and recorded context-window data used by the fit engine.
Last verified: 2026-09-25
LM Studio
LM Studio system requirements
Used to verify Windows x64, AVX2, RAM, and dedicated-VRAM guidance.
Last verified: 2026-09-26
LM Studio Community
LM Studio GGUF model data
Recorded GGUF variant size and quantization data used by the LM Studio fit engine.
Last verified: 2026-09-26
PyTorch
PyTorch Windows CUDA compatibility
Official evidence used for the Windows and NVIDIA CUDA hardware compatibility path.
Last verified: 2026-09-26
ComfyUI
ComfyUI compatibility
Official ComfyUI installation and NVIDIA support evidence.
Last verified: 2026-09-25
ComfyUI
ComfyUI workflow evidence
Official workflow example used alongside model-file data.
Last verified: 2026-09-25
Verified compatibility
Application support is kept separate from model-fit and workflow-memory heuristics.
Honest memory signals
Model file sizes are not presented as official VRAM requirements. Offloading and uncertainty stay visible.
No forced upgrades
If the verified workloads do not show a meaningful hardware bottleneck, the advisor says no upgrade is needed.