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This video documents a controlled repaste procedure on an Nvidia GeForce RTX 3080 Gigabyte Eagle, focused on measurable thermal optimization. Full dataset can be accessed here: https://tinyurl.com/48j45ssp The goal was to quantify available thermal margin and the effect of improved interface contact on VRAM junction temperature, GPU stability and system behavior. Baseline testing was performed twice before intervention: – GPU fans auto controlled – GPU fans locked at 100 percent During disassembly, a 0.7 mm difference between compressed and uncompressed VRAM pad regions was observed. Pad strategy was evaluated carefully, as in many RTX 3080 designs certain pads act as heatsink alignment spacers and must not be replaced. Modification: – KRYO33 across the full GPU die – K5 PRO Mt. Olympos Edition on VRAM – UV inspection to confirm full gap coverage – Correction of dark corners to eliminate incomplete contact Post-mod validation used the same dual benchmark method for direct comparison. Performance gain appears moderate but is not negligible. Benchmark improvement aligns with a 2.5 percent increase in GPU maximum power draw, indicating that before the intervention the card was intermittently power-limited by thermal constraints. In other words, brief thermal throttling events were occurring, contributing to cumulative stress. Before modification, GPU and VRAM operated within specification but near upper limits. After repaste, operating temperatures moved significantly further from those thresholds. The benefit is not only lower temperature, but improved reliability and longer component lifespan. With automatic control, fan utilization decreased by 6.2 percent, translating to nearly half the perceived acoustic annoyance. Thermal efficiency therefore improves both mechanical stress and noise behavior. The entire motherboard area was monitored with a thermal imaging camera during benchmarking. This parallel dataset allows observation of how GPU thermal behavior influences neighboring components. Early evidence shows measurable impact on system RAM and surrounding circuitry when the GPU operates at sustained high fan speeds. Increased airflow and localized heat flux alter thermal gradients. A healthier system state is achieved not only by lower temperature, but by reduced fan demand and turbulence. All procedures, including baseline, repaste and validation, were completed within five hours on the same day (ambient 20.2°C to 20.6°C). KRYO33 and K5 PRO Mt. Olympos Edition are engineered to function as a system. No curing or stabilization period is required. With proper, symmetrical mounting pressure, performance is measurable from first power-on. KRYO33 contains only solid thermally conductive particles and no silicone oil. It must therefore be applied across the entire GPU surface. K5 PRO Mt. Olympos Edition, though viscous, is highly elastic under compression. It allows the heatsink to approach VRAM to minimum gap distance while excess material displaces outward without later flow. Other putties may behave differently. These materials are engineered specifically for this application. Follow the demonstrated method. Performance gain is measurable. Thermal reduction is substantial. Longevity improvement is strategic. This experiment is the first entry in a structured test series designed to generate validated datasets for AI-assisted evaluation of thermal interface quality and system-level thermal interaction. validated datasets for future AI-assisted evaluation of thermal interface application quality, throttling behavior and system-level thermal interaction. Chapters 00:00 Baseline Benchmarking 11:00 GPU Disassembly and Thermal Pad Inspection 13:00 VRAM Pad Replacement 15:00 KRYO33 Application on GPU Core 17:00 K5 PRO Mt. Olympos Edition Application on VRAM 22:20 UV Inspection and Gap Optimization 26:00 Reassembly and Post-Modification Testing 30:00 Results: Performance vs Thermal Products used K5 PRO Mt. Olympos Edition: https://computer-systems.gr/products/... KRYO33 : https://computer-systems.gr/products/... The experiment presented in this video was conducted as part of the project "Data Recovery and Remote Computer Diagnostic Services with AI" (Application Code: ΕΚΠΑΡ01-0063510), funded under the strategic action "Research - Innovate" of the "Competitiveness" Programme. The project is co-financed by Greece and the European Union through the European Regional Development Fund (ERDF). Beneficiary: Karydopoulos Panagiotis Andreas (Computer Systems) Framework: ESPA 2021-2027 Find us on: Facebook ► https://bit.ly/2V58aey Instagram ► https://bit.ly/32bHg6h Youtube ► https://bit.ly/2SGCWJg Google ► https://bit.ly/2vU9uaf Twitter ► https://bit.ly/2SJK6N1 http://computer-systems.gr