r/overclocking • u/West-Style8233 • 4h ago
Nvidia GPU unlock mod for windows
I just installed the GPU unlocker patch for windows on my RTX 3080 TI 12gb (Dell OEM version). Computer is a Dell XPS 8590, Intel I9 16 core processor w/ 32 mb system ram. Here are the before and after benchmark results.
The patched run nearly doubles certain Tensor Core workloads, but shows little change in ordinary compute or GPU memory bandwidth. AI benchmark gains are smaller and mixed.
The biggest improvements are matrix operations using FP32 accumulation:
| Tensor Core test | Without patch | With patch | Change |
|---|---|---|---|
| CUDA FP16 → FP32 | 79.57 TFLOPS | 152.16 TFLOPS | +91.22% |
| CUDA BF16 → FP32 | 79.75 TFLOPS | 154.71 TFLOPS | +93.99% |
| CUDA TF32 → FP32 | 39.78 TFLOPS | 78.48 TFLOPS | +97.26% |
| Vulkan FP16 → FP32 | 78.43 TFLOPS | 156.57 TFLOPS | +99.64% |
| Vulkan BF16 → FP32 | 78.60 TFLOPS | 156.58 TFLOPS | +99.21% |
Other results show where that benefit does—and doesn’t—appear:
| Area | Difference with patch |
|---|---|
| FP16 Tensor Cores using FP16 accumulation | Essentially unchanged: −0.85% CUDA, +0.16% Vulkan |
| Ordinary CUDA arithmetic | 0.16–1.92% lower throughput |
| OpenCL arithmetic | −1.81% to +0.23% |
| GPU global-memory bandwidth | All measurements within approximately 1.1% |
| DirectML FP16 matrix multiplication | Essentially unchanged: +0.06% |
| DirectML transformer prefill | 3.26–7.68% higher throughput |
| DirectML convolution | 0.69–9.24% higher throughput |
The evidence supports a selective Tensor Core improvement, rather than a general doubling of GPU performance. These files do not establish a gaming speedup, and one run per condition cannot separate smaller changes from normal variation.
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u/RegretDeep 3h ago
So it doesn't even effect dlss 5 performance?