Micro-Star International Co., Ltd. MS-7D77
Geekbench AI Score
31892
Single Precision Score
54536
Half Precision Score
24358
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | August 15 2025 10:52 AM |
| Views | 3 |
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 | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13520
2.51 KIPS |
|
|
Image Classification (HP)
|
100% |
20497
3.81 KIPS |
|
|
Image Classification (Q)
|
100% |
11851
2.20 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20773
336.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
28661
464.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
19325
314.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
170128
198.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
655385
764.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
153718
180.1 IPS |
|
|
Object Detection (SP)
|
100% |
16852
1.34 KIPS |
|
|
Object Detection (HP)
|
100% |
27942
2.22 KIPS |
|
|
Object Detection (Q)
|
86% |
14214
1.14 KIPS |
|
|
Face Detection (SP)
|
100% |
48087
571.4 IPS |
|
|
Face Detection (HP)
|
100% |
67255
799.1 IPS |
|
|
Face Detection (Q)
|
97% |
39470
470.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
84771
653.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
144365
1.11 KIPS |
|
|
Depth Estimation (Q)
|
78% |
62917
502.4 IPS |
|
|
Style Transfer (SP)
|
100% |
309579
398.0 IPS |
|
|
Style Transfer (HP)
|
100% |
983126
1.26 KIPS |
|
|
Style Transfer (Q)
|
98% |
257544
332.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
47302
1.75 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
79051
2.92 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
35895
1.33 KIPS |
|
|
Text Classification (SP)
|
100% |
3890
5.19 KIPS |
|
|
Text Classification (HP)
|
100% |
4924
6.57 KIPS |
|
|
Text Classification (Q)
|
97% |
2326
3.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
5823
100.3 IPS |
|
|
Machine Translation (HP)
|
100% |
5823
100.3 IPS |
|
|
Machine Translation (Q)
|
70% |
2752
51.6 IPS |
