NVIDIA's DLSS 5 neural rendering technology has garnered significant attention in the tech community due to the leak of its core DLL files, prompting developers worldwide to explore its capabilities. A development team attempted to combine FP8 and NVFP4 low-precision formats and apply them to the DLSS 5 model, conducting tests on RTX 50 series graphics cards. Despite leveraging the native support for NVFP4 by the Tensor Cores in the Blackwell architecture, the performance gains were minimal. At 4K resolution, the time consumption during the neural rendering phase was optimized by only 1%-2%, and in tests with Baldur's Gate 3, the frame rate increased by just 1.08%. Additionally, the current solution cannot achieve full-process NVFP4 computation coverage. The 0.7.2 version of the OptiScaler-DLSSNR-PreSR-Multipass project optimized the mixed-precision path, listing NVFP4 as the recommended configuration for Blackwell architecture graphics cards, but its impact on overall game performance remains limited. Industry experts point out that optimizing DLSS 5 faces multiple challenges, including model architecture, quantization strategies, and driver adaptation. Although NVIDIA officially claims that its runtime speed has improved fivefold compared to the first demonstration and supports RTX 40 series graphics cards, community tests indicate that existing optimization solutions have yet to achieve a revolutionary breakthrough. Currently, developers worldwide are still exploring more efficient optimization solutions, such as model compression and dynamic precision adjustment, to drive the field of real-time rendering toward greater efficiency.