Micro-Star International Co., Ltd. MS-7D31
Geekbench AI Score
31792
Single Precision Score
46403
Half Precision Score
24145
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Rikzzz87 |
| Upload Date | September 08 2024 03:38 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D31 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z690 EDGE WIFI (MS-7D31) |
| Power Plan | Equilibrado |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600KF |
| 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% |
12538
2.33 KIPS |
|
|
Image Classification (HP)
|
99% |
17696
3.30 KIPS |
|
|
Image Classification (Q)
|
100% |
10571
1.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
19076
309.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
23637
383.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
17666
287.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
255648
298.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
485404
566.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
225939
264.6 IPS |
|
|
Object Detection (SP)
|
100% |
15018
1.19 KIPS |
|
|
Object Detection (HP)
|
100% |
21506
1.71 KIPS |
|
|
Object Detection (Q)
|
89% |
12305
985.1 IPS |
|
|
Face Detection (SP)
|
100% |
39963
474.9 IPS |
|
|
Face Detection (HP)
|
100% |
50156
596.0 IPS |
|
|
Face Detection (Q)
|
97% |
34046
405.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
75324
580.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
144293
1.11 KIPS |
|
|
Depth Estimation (Q)
|
76% |
56979
459.0 IPS |
|
|
Style Transfer (SP)
|
100% |
385964
496.2 IPS |
|
|
Style Transfer (HP)
|
100% |
879847
1.13 KIPS |
|
|
Style Transfer (Q)
|
98% |
337981
435.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
54702
2.02 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
74505
2.75 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
40517
1.50 KIPS |
|
|
Text Classification (SP)
|
100% |
3793
5.06 KIPS |
|
|
Text Classification (HP)
|
99% |
4646
6.20 KIPS |
|
|
Text Classification (Q)
|
97% |
2313
3.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
4766
82.1 IPS |
|
|
Machine Translation (HP)
|
100% |
4810
82.9 IPS |
|
|
Machine Translation (Q)
|
60% |
2111
47.1 IPS |
