How does the AI hardware analyzer detect my GPU?

The analyzer uses WebGL's WEBGL_debug_renderer_info extension to read your GPU model name directly from the browser. It then matches against a database of 100+ GPUs to look up VRAM, compute cores, and performance tier. If WebGPU is available, additional capabilities are detected.

Is this hardware scan accurate?

Browser-based detection has inherent limitations compared to native tools. GPU detection is highly accurate (exact model match in most cases). CPU core count is exact. RAM estimation uses multiple signals and is typically within 20% of actual. Storage and network tests reflect real throughput. The overall score provides a reliable relative assessment of AI readiness.

100% private. All hardware detection and benchmarks run entirely in your browser. The only network request is the speed test, which downloads random bytes from our server. No hardware data is ever transmitted. Results are cached locally in IndexedDB.

What hardware do I need for AI development?

It depends on your use case. For API-based AI development, almost any modern computer works. For running local LLMs (7B models), you need 8GB+ VRAM and 16GB+ RAM. For fine-tuning and training, you need 16GB+ VRAM (RTX 4080/4090 or better), 32GB+ RAM, and fast NVMe storage. The analyzer evaluates your specific hardware against these requirements.

Can I use this on mobile?

The analyzer works in any modern browser, but it's designed for desktop and laptop computers. Mobile devices don't have the GPU VRAM and processing power needed for local AI development, so the tool will show a message recommending desktop use.

FREE TOOL

AI Hardware Readiness Analyzer

One click. Full analysis. Find out if your hardware is ready for AI development (GPU, CPU, RAM, storage, and network) with personalized upgrade recommendations.

100% Browser-Based

No Downloads Required

No Data Collected

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