X570M Pro4
Geekbench AI Score
29159
Single Precision Score
47377
Half Precision Score
21073
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | August 31 2025 07:05 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | X570M Pro4 |
| Motherboard | ASRock X570M Pro4 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 0 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12244
2.28 KIPS |
|
|
Image Classification (HP)
|
100% |
17558
3.27 KIPS |
|
|
Image Classification (Q)
|
100% |
4750
883.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
17822
288.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
22657
367.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
17018
276.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
171847
200.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
641295
748.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
154308
180.7 IPS |
|
|
Object Detection (SP)
|
100% |
15119
1.20 KIPS |
|
|
Object Detection (HP)
|
100% |
22505
1.79 KIPS |
|
|
Object Detection (Q)
|
86% |
12596
1.01 KIPS |
|
|
Face Detection (SP)
|
100% |
43529
517.2 IPS |
|
|
Face Detection (HP)
|
100% |
59605
708.2 IPS |
|
|
Face Detection (Q)
|
97% |
36687
437.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
83105
640.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
142245
1.10 KIPS |
|
|
Depth Estimation (Q)
|
78% |
63088
503.8 IPS |
|
|
Style Transfer (SP)
|
100% |
305581
392.8 IPS |
|
|
Style Transfer (HP)
|
100% |
904039
1.16 KIPS |
|
|
Style Transfer (Q)
|
98% |
257026
331.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
44282
1.64 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
70097
2.59 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
34547
1.28 KIPS |
|
|
Text Classification (SP)
|
100% |
3212
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3671
4.90 KIPS |
|
|
Text Classification (Q)
|
97% |
2082
2.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
4985
85.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5032
86.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2569
48.2 IPS |
