Micro-Star International Co., Ltd. MS-7C95
Geekbench ML Score
7992
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 02:44 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7C95 |
| Motherboard | Micro-Star International Co., Ltd. B550M PRO-VDH WIFI (MS-7C95) |
| Power Plan | Alto desempenho |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 512 KB x 8 |
| L3 Cache | 32.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce GTX 1660 Ti |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3996
747.8 IPS |
|
|
Image Classification (F16)
|
100% |
3999
748.2 IPS |
|
|
Image Classification (I8)
|
100% |
3129
585.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
6076
101.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
6047
101.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
5070
84.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
37777
45.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
37742
45.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
39317
47.6 IPS |
|
|
Object Detection (F32)
|
100% |
3514
262.4 IPS |
|
|
Object Detection (F16)
|
100% |
3102
231.6 IPS |
|
|
Object Detection (I8)
|
60% |
2685
200.5 IPS |
|
|
Face Detection (F32)
|
100% |
10510
125.0 IPS |
|
|
Face Detection (F16)
|
100% |
10509
125.0 IPS |
|
|
Face Detection (I8)
|
89% |
8292
98.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
23729
184.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
23763
184.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
17864
138.5 IPS |
|
|
Style Transfer (F32)
|
100% |
78013
102.6 IPS |
|
|
Style Transfer (F16)
|
100% |
64210
84.5 IPS |
|
|
Style Transfer (I8)
|
98% |
66038
86.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13032
465.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13016
464.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8331
297.5 IPS |
|
|
Text Classification (F32)
|
100% |
1363
1.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1366
1.96 KIPS |
|
|
Text Classification (I8)
|
98% |
788
1.13 KIPS |
|
|
Machine Translation (F32)
|
100% |
2960
54.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2955
54.4 IPS |
|
|
Machine Translation (I8)
|
70% |
1425
26.2 IPS |
