GPU Buying Comparison Panel

Align scattered GPU specs, configs, and prices into one filterable table

Problem

Anyone buying a GPU for AI workloads has to juggle datasheets from Nvidia, AMD, and Huawei while also matching full-system configs, vendors, and prices. The information is scattered and inconsistent, making comparison painful. Existing tools are either vendor marketing pages or scattered reviews with no workload-based filtering.

Solution

A GPU database focused on comparison and purchasability: align vendor specs, system configs, third-party vendor prices, and public benchmarks; filter by VRAM, bandwidth, power, and price; source every data point. Users can save comparison lists and subscribe to price or config alerts. Data comes from community submissions plus scraping scripts.

Users

Indie developers, small labs, and startup engineers buying AI training/inference hardware, plus hardware enthusiasts doing selection.

MVP

Structured GPU spec database; workload-based filters and comparison table; linked system configs and vendor prices; source attribution for every record; community submission flow.

Revenue

Free browsing plus paid price alerts and exportable reports; vendor listing fees or affiliate links; one-time custom selection reports for enterprises.

Why now

The AI hardware market is extremely fragmented, with Huawei, AMD, and others entering fast, while specs and prices shift quickly and existing comparison tools lag badly. An indie dev can build a small, accurate vertical database and keep it fresh with community contributions.