Technology

Modder pushes rare 20GB RTX 3080 Ti past 550W with risky power shunts and liquid metal cooling — project reveals full performance potential of the unreleased GPU sample

Source

Tom's Hardware

Published

Feb 25, 2026

TL;DR

AI Generated

A modder has pushed a rare 20GB Nvidia GeForce RTX 3080 Ti past 550W by using risky power shunts and liquid metal cooling, revealing the GPU's full performance potential. The modder acquired the engineering sample for $700 and embarked on a detailed modding project, increasing power draw and addressing cooling issues. Despite challenges with heat management and memory temperatures, the modder successfully enhanced the GPU's performance, making it behave more like a 3080 Ti class GPU. This experimental exploration showcases the capabilities of the unreleased GPU sample but may not have practical value beyond collectors or tech enthusiasts.

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Modder pushes rare 20GB RTX 3080 Ti past 550W with risky power shunts and liquid metal cooling — project reveals full performance potential of the unreleased GPU sample

TL;DR

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Lexar regional manager says that RAM prices are expected to double by the end of the year — 'discounts' and stabilized prices result from distributors getting rid of old stock or sourcing products from other regions

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Modder pushes rare 20GB RTX 3080 Ti past 550W with risky power shunts and liquid metal cooling — project reveals full performance potential of the unreleased GPU sample

TL;DR

Similar Articles

Lexar regional manager says that RAM prices are expected to double by the end of the year — 'discounts' and stabilized prices result from distributors getting rid of old stock or sourcing products from other regions

Taiwanese startup FormulaV Line wants to break into US market with two new unique cases — company expects products to become available on Newegg later this year

G.Skill explains how AMD EXPO ULL unlocks additional performance — expanded profiles allow memory makers to include subtiming tweaks for the first time

Huawei-led team claims it post-trained DeepSeek's 1.6-trillion-parameter model — 1,000 Ascend 910C chips used in training