Use this calculator to estimate whether your computer can run a local AI model before you download it. It considers system RAM, dedicated GPU VRAM, Mac unified memory, model size, quantization, context length, runtime overhead, and a beginner safety margin.
Conservative estimate, not a benchmark. It does not predict measured throughput, answer quality, thermals, driver issues, or whether a specific model file will behave well in a specific app.
Actual results depend on model, quantization, context length, runtime, GPU offload, drivers, thermals, and other running apps. Local AI Guide has not independently benchmarked this hardware.
| Result | Meaning | Next step |
|---|---|---|
| Likely fits | The selected setup appears to have enough memory headroom under the calculator assumptions. | Try a small or medium model first and document your actual result if you need proof. |
| Tight fit | The setup may work but has limited headroom. | Lower context, choose a smaller quantization/model, close other apps, or use a stronger machine. |
| Unlikely fit | The selected setup probably exceeds the practical memory budget. | Use a smaller model, reduce context, or move to more RAM/VRAM. |
| Unknown | The calculator lacks enough reliable assumptions. | Treat the result as a research prompt, not a recommendation. |
An 8GB laptop should usually start with small 3B or 4B-class models and modest context. Do not treat 7B/8B models as a comfortable default unless you test the exact setup.
A 16GB Apple Silicon Mac is a practical beginner tier, but unified memory is shared with macOS and other apps. Start with a 7B/8B-class model and avoid heavy multitasking during early use.
A desktop GPU with 24GB dedicated VRAM is a higher-headroom local AI tier. It can make 32B-class quantized models more realistic, but context length, runtime overhead, and model format still matter.
The current calculator is implemented as a client-side estimator. The share URL stores selected settings in the URL. If analytics or server-side logging are added later, the page must disclose that behavior clearly.
Real local AI behavior depends on model file format, quantization, GPU offload, drivers, thermals, background apps, runtime implementation, context length, and exact model architecture. A memory estimate is useful, but it is not the same as a lab benchmark.
No. Use the calculator as a first filter, then confirm with current benchmarks, return policies, and your actual workflow.