Micro-Star International Co., Ltd. MS-7D77
Geekbench AI Score
32400
Single Precision Score
55195
Half Precision Score
24791
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | August 08 2025 12:12 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 | 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% |
13901
2.59 KIPS |
|
|
Image Classification (HP)
|
100% |
20960
3.90 KIPS |
|
|
Image Classification (Q)
|
100% |
12342
2.30 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20799
337.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
28055
454.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
19145
311.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
172910
201.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
674548
787.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
156825
183.7 IPS |
|
|
Object Detection (SP)
|
100% |
17130
1.36 KIPS |
|
|
Object Detection (HP)
|
100% |
27733
2.20 KIPS |
|
|
Object Detection (Q)
|
86% |
14314
1.15 KIPS |
|
|
Face Detection (SP)
|
100% |
47847
568.5 IPS |
|
|
Face Detection (HP)
|
100% |
67019
796.3 IPS |
|
|
Face Detection (Q)
|
97% |
39548
471.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
85869
661.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
149907
1.15 KIPS |
|
|
Depth Estimation (Q)
|
78% |
63998
511.0 IPS |
|
|
Style Transfer (SP)
|
100% |
317794
408.5 IPS |
|
|
Style Transfer (HP)
|
100% |
1014038
1.30 KIPS |
|
|
Style Transfer (Q)
|
98% |
264795
341.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
47993
1.77 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
78879
2.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36960
1.37 KIPS |
|
|
Text Classification (SP)
|
100% |
4134
5.52 KIPS |
|
|
Text Classification (HP)
|
100% |
5185
6.92 KIPS |
|
|
Text Classification (Q)
|
97% |
2411
3.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
5747
99.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5726
98.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2769
51.9 IPS |
