Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

VRAMGlass

Find the right GPU for running LLMs locally

Details

External ID
1254597
Source
PH
Company
—
Product
VRAMGlass
Website domain
producthunt.com
Launched
Sept. 19, 2026
Cohort
—
Upvotes
1
Upvotes percentile
0.30815693820825313
Tags
Hardware, Developer Tools, Artificial Intelligence
Fetched at
Sept. 21, 2026, 1:01 a.m.
Updated at
Sept. 21, 2026, 1:01 a.m.

Description

Pick an open-weight model and a quantization, see how much memory it needs, and find the GPUs that fit. Then check what those cards actually list for: used on eBay (US) and Xianyu (China), new on Amazon Japan, with price history, sample counts and freshness labels. Plus RAM prices, a GPU price index, plain-English guides, and an embeddable live price card with an MIT-licensed SDK. Free, no sign-up, 4 languages.

Enrichment

Theme
lightweight and on-device AI runtimes
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
gpu calculator for running local llms
Manually corrected
False

Could you build this?

Partial The memory calculator formula and frontend are easy to vibe-code, but continuously scraping localized marketplace pricing (like Xianyu and Amazon JP) with anti-bot defenses requires dedicated scraper maintenance.

What it would actually take: The frontend is a standard Next.js calculator querying Hugging Face model architectures to compute VRAM (weights + KV cache + context). The hard part is building and maintaining robust headless browser scrapers (e.g., Playwright with proxy pools and captcha solvers) to harvest live listing prices from Xianyu (Alibaba ecosystem) and eBay, storing timeseries price histories in Postgres.

Competitors

Other products that read as similar to this one — 120 launches clear the similarity bar, closest 8 shown.

Attention rank: #87 of 121 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 315 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.