Micro-Star International Co., Ltd. MS-7D77
Geekbench AI Score
35148
Single Precision Score
61419
Half Precision Score
26423
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | August 20 2025 07:18 AM |
| Views | 2 |
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 | Micro-Star International Co., Ltd. MS-7D77 |
| Motherboard | Micro-Star International Co., Ltd. PRO B650M-A WIFI (MS-7D77) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 9700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
14503
2.70 KIPS |
|
|
Image Classification (HP)
|
100% |
22594
4.20 KIPS |
|
|
Image Classification (Q)
|
100% |
12705
2.36 KIPS |
|
|
Image Segmentation (SP)
|
100% |
25493
413.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
37245
603.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
23029
374.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
181242
211.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
728969
850.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
162750
190.6 IPS |
|
|
Object Detection (SP)
|
100% |
18421
1.46 KIPS |
|
|
Object Detection (HP)
|
100% |
30703
2.44 KIPS |
|
|
Object Detection (Q)
|
86% |
15235
1.22 KIPS |
|
|
Face Detection (SP)
|
100% |
54513
647.7 IPS |
|
|
Face Detection (HP)
|
100% |
80185
952.8 IPS |
|
|
Face Detection (Q)
|
97% |
44622
532.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
89100
686.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
159103
1.23 KIPS |
|
|
Depth Estimation (Q)
|
78% |
66941
534.5 IPS |
|
|
Style Transfer (SP)
|
100% |
327257
420.7 IPS |
|
|
Style Transfer (HP)
|
100% |
1057272
1.36 KIPS |
|
|
Style Transfer (Q)
|
98% |
271111
349.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49590
1.83 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
81911
3.02 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37612
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
4144
5.53 KIPS |
|
|
Text Classification (HP)
|
100% |
5173
6.90 KIPS |
|
|
Text Classification (Q)
|
97% |
2448
3.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
7137
122.9 IPS |
|
|
Machine Translation (HP)
|
100% |
7097
122.2 IPS |
|
|
Machine Translation (Q)
|
70% |
3067
57.5 IPS |
