Micro-Star International Co., Ltd. MS-7E16
Geekbench AI Score
38897
Single Precision Score
67183
Half Precision Score
28767
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | May 09 2025 11:19 PM |
| Views | 10 |
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% |
15872
2.95 KIPS |
|
|
Image Classification (HP)
|
100% |
23839
4.43 KIPS |
|
|
Image Classification (Q)
|
100% |
13769
2.56 KIPS |
|
|
Image Segmentation (SP)
|
100% |
30021
486.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
46157
748.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
26734
434.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
197713
230.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
766209
894.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
177892
208.4 IPS |
|
|
Object Detection (SP)
|
100% |
20278
1.61 KIPS |
|
|
Object Detection (HP)
|
100% |
34222
2.71 KIPS |
|
|
Object Detection (Q)
|
86% |
16401
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
60105
714.2 IPS |
|
|
Face Detection (HP)
|
100% |
85871
1.02 KIPS |
|
|
Face Detection (Q)
|
97% |
47955
571.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
95845
738.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
158327
1.22 KIPS |
|
|
Depth Estimation (Q)
|
78% |
69691
556.5 IPS |
|
|
Style Transfer (SP)
|
100% |
366700
471.4 IPS |
|
|
Style Transfer (HP)
|
100% |
1168560
1.50 KIPS |
|
|
Style Transfer (Q)
|
98% |
300588
387.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55593
2.05 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
91609
3.38 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
41433
1.53 KIPS |
|
|
Text Classification (SP)
|
100% |
4295
5.73 KIPS |
|
|
Text Classification (HP)
|
100% |
5396
7.20 KIPS |
|
|
Text Classification (Q)
|
97% |
2586
3.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
8229
141.8 IPS |
|
|
Machine Translation (HP)
|
100% |
8268
142.4 IPS |
|
|
Machine Translation (Q)
|
70% |
3358
63.0 IPS |
