Micro-Star International Co., Ltd. MS-7D99
Geekbench AI Score
28512
Single Precision Score
49294
Half Precision Score
22047
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 20 2025 02:19 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D99 |
| Motherboard | Micro-Star International Co., Ltd. B760M GAMING PLUS WIFI (MS-7D99) |
| CPU Information | |
|---|---|
| Name | Intel Core i5-14600KF |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11319
2.11 KIPS |
|
|
Image Classification (HP)
|
100% |
19192
3.57 KIPS |
|
|
Image Classification (Q)
|
100% |
10015
1.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20743
336.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
30095
487.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
18486
300.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
167300
195.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
467189
545.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
142282
166.7 IPS |
|
|
Object Detection (SP)
|
100% |
14740
1.17 KIPS |
|
|
Object Detection (HP)
|
100% |
24042
1.91 KIPS |
|
|
Object Detection (Q)
|
83% |
12478
1.01 KIPS |
|
|
Face Detection (SP)
|
100% |
38613
458.8 IPS |
|
|
Face Detection (HP)
|
100% |
55540
659.9 IPS |
|
|
Face Detection (Q)
|
97% |
32600
388.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
68207
525.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
130090
1.00 KIPS |
|
|
Depth Estimation (Q)
|
78% |
54164
432.3 IPS |
|
|
Style Transfer (SP)
|
100% |
231079
297.1 IPS |
|
|
Style Transfer (HP)
|
100% |
778366
1.00 KIPS |
|
|
Style Transfer (Q)
|
98% |
198831
256.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
41922
1.55 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
78766
2.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
33730
1.25 KIPS |
|
|
Text Classification (SP)
|
100% |
4037
5.39 KIPS |
|
|
Text Classification (HP)
|
100% |
4913
6.56 KIPS |
|
|
Text Classification (Q)
|
97% |
2482
3.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
5954
102.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6001
103.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2809
52.7 IPS |
