ShellNewHandler VS VRAMGlass

VRAMGlass's answer:

VRAMGlass brings GPU specifications, model memory planning and market-specific price references into one free web tool for local AI. You can compare VRAM capacity, memory bandwidth and power, explore quantized model weight sizes, and review price histories with sample counts, observation dates and freshness labels.

US used listings on eBay, Chinese used listings on Xianyu and Japanese new offers on Amazon.co.jp are kept as separate market references. Display currency is a separate choice. Methodology notes explain the calculations and their limits: asking prices are not completed sales, and model-fit estimates are planning aids rather than guaranteed benchmarks.

VRAMGlass's answer:

VRAMGlass is designed for developers running large language models locally, hardware enthusiasts comparing GPUs, and people planning a local AI workstation or upgrade. It helps users connect model size and quantization with VRAM and system RAM requirements, then compare hardware specifications and market-specific price references.

Practical guides also help people who are new to local AI understand VRAM, quantization, context memory and offloading.

VRAMGlass's answer:

VRAMGlass is a useful choice if you want to connect model memory requirements with GPU specifications and hardware budgets in one place. Start with a model and quantization, estimate the memory you need, compare GPUs, and review the relevant market price references.

It is free to use and available in English, Simplified Chinese, Traditional Chinese and Japanese. The focus is on transparent planning: source methodology, sample dates and price freshness help you judge the data before making a decision. Use it alongside workload-specific testing, since actual performance depends on your model, runtime and configuration.

VRAMGlass's answer:

VRAMGlass is an independent one-person project founded in August 2026 and maintained by voltwake in Hong Kong. It focuses on a practical question: how can someone choose hardware for the models they want to run locally?

The project brings GPU comparisons, model memory estimates and market-specific price references together, supported by methodology notes and practical guides. Its purpose is to make local AI hardware planning easier to understand while being clear about the limits of price data and estimates.

VRAMGlass's answer:

VRAMGlass is built with Astro and TypeScript, with Cloudflare Workers providing the web runtime and Cloudflare D1 providing database storage. It is delivered as a browser-based tool.