Micro-Star International Co., Ltd. MS-7E24
Geekbench AI Score
29108
Single Precision Score
51229
Half Precision Score
22543
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | June 20 2025 07:37 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E24 |
| Motherboard | Micro-Star International Co., Ltd. B650M GAMING PLUS WIFI (MS-7E24) |
| 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% |
11796
2.19 KIPS |
|
|
Image Classification (HP)
|
100% |
20443
3.80 KIPS |
|
|
Image Classification (Q)
|
100% |
10634
1.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
19003
308.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
27367
443.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
17987
292.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
168809
197.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
481172
561.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
144574
169.3 IPS |
|
|
Object Detection (SP)
|
100% |
15956
1.27 KIPS |
|
|
Object Detection (HP)
|
100% |
27506
2.18 KIPS |
|
|
Object Detection (Q)
|
83% |
13278
1.07 KIPS |
|
|
Face Detection (SP)
|
100% |
41499
493.1 IPS |
|
|
Face Detection (HP)
|
100% |
61346
728.9 IPS |
|
|
Face Detection (Q)
|
97% |
34587
412.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
71579
551.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
136023
1.05 KIPS |
|
|
Depth Estimation (Q)
|
78% |
55708
444.7 IPS |
|
|
Style Transfer (SP)
|
100% |
233850
300.6 IPS |
|
|
Style Transfer (HP)
|
100% |
809628
1.04 KIPS |
|
|
Style Transfer (Q)
|
98% |
199800
257.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
43786
1.62 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
83535
3.08 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
34664
1.28 KIPS |
|
|
Text Classification (SP)
|
100% |
4179
5.58 KIPS |
|
|
Text Classification (HP)
|
100% |
5147
6.87 KIPS |
|
|
Text Classification (Q)
|
97% |
2507
3.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
5691
98.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5789
99.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2760
51.8 IPS |
