Micro-Star International Co., Ltd. MS-7D29
Geekbench AI Score
38792
Single Precision Score
65295
Half Precision Score
29132
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 30 2025 04:17 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D29 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z690I UNIFY (MS-7D29) |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900K |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 48.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15178
2.82 KIPS |
|
|
Image Classification (HP)
|
100% |
22769
4.23 KIPS |
|
|
Image Classification (Q)
|
100% |
13394
2.49 KIPS |
|
|
Image Segmentation (SP)
|
100% |
30387
492.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
43772
709.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
26939
438.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
243135
283.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
762507
889.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
207879
243.5 IPS |
|
|
Object Detection (SP)
|
100% |
19711
1.56 KIPS |
|
|
Object Detection (HP)
|
100% |
30086
2.39 KIPS |
|
|
Object Detection (Q)
|
86% |
16758
1.35 KIPS |
|
|
Face Detection (SP)
|
100% |
56259
668.5 IPS |
|
|
Face Detection (HP)
|
100% |
80956
961.9 IPS |
|
|
Face Detection (Q)
|
97% |
46382
553.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
92880
715.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
177229
1.37 KIPS |
|
|
Depth Estimation (Q)
|
78% |
68871
550.0 IPS |
|
|
Style Transfer (SP)
|
100% |
359227
461.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1178920
1.52 KIPS |
|
|
Style Transfer (Q)
|
98% |
309268
398.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
59239
2.19 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
90951
3.36 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
44294
1.64 KIPS |
|
|
Text Classification (SP)
|
100% |
4199
5.60 KIPS |
|
|
Text Classification (HP)
|
100% |
5375
7.17 KIPS |
|
|
Text Classification (Q)
|
97% |
2531
3.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
7477
128.8 IPS |
|
|
Machine Translation (HP)
|
100% |
7451
128.3 IPS |
|
|
Machine Translation (Q)
|
70% |
3163
59.3 IPS |
