Micro-Star International Co., Ltd. MS-7E16
Geekbench AI Score
38447
Single Precision Score
66764
Half Precision Score
28801
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | April 13 2025 01:34 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 IoT Enterprise LTSC (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E16 |
| Motherboard | Micro-Star International Co., Ltd. X670E GAMING PLUS WIFI (MS-7E16) |
| Power Plan | Utilisation normale |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 9900X 12-Core Processor |
| Topology | 1 Processor, 12 Cores, 24 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 4.40 GHz |
| Cluster 1 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15540
2.89 KIPS |
|
|
Image Classification (HP)
|
100% |
23692
4.41 KIPS |
|
|
Image Classification (Q)
|
100% |
13635
2.54 KIPS |
|
|
Image Segmentation (SP)
|
100% |
29778
482.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
45808
742.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
26844
436.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
194766
227.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
762114
889.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
174407
204.3 IPS |
|
|
Object Detection (SP)
|
100% |
20058
1.59 KIPS |
|
|
Object Detection (HP)
|
100% |
33546
2.66 KIPS |
|
|
Object Detection (Q)
|
86% |
16394
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
59513
707.1 IPS |
|
|
Face Detection (HP)
|
100% |
85410
1.01 KIPS |
|
|
Face Detection (Q)
|
97% |
48356
576.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
97325
749.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
156645
1.21 KIPS |
|
|
Depth Estimation (Q)
|
78% |
72126
575.9 IPS |
|
|
Style Transfer (SP)
|
100% |
360636
463.6 IPS |
|
|
Style Transfer (HP)
|
100% |
1180172
1.52 KIPS |
|
|
Style Transfer (Q)
|
98% |
298333
384.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55460
2.05 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
90482
3.34 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
41774
1.55 KIPS |
|
|
Text Classification (SP)
|
100% |
4236
5.65 KIPS |
|
|
Text Classification (HP)
|
100% |
5352
7.14 KIPS |
|
|
Text Classification (Q)
|
97% |
2553
3.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
7955
137.0 IPS |
|
|
Machine Translation (HP)
|
100% |
8295
142.9 IPS |
|
|
Machine Translation (Q)
|
70% |
3382
63.4 IPS |
