Micro-Star International Co., Ltd. MS-7C95
Geekbench ML Score
8300
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 02:45 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% |
4004
749.2 IPS |
|
|
Image Classification (F16)
|
100% |
4023
752.8 IPS |
|
|
Image Classification (I8)
|
100% |
3149
589.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
6858
114.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
6078
101.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
5073
84.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
38030
46.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
46251
56.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
39796
48.2 IPS |
|
|
Object Detection (F32)
|
100% |
3527
263.3 IPS |
|
|
Object Detection (F16)
|
100% |
3505
261.6 IPS |
|
|
Object Detection (I8)
|
60% |
3089
230.6 IPS |
|
|
Face Detection (F32)
|
100% |
10575
125.7 IPS |
|
|
Face Detection (F16)
|
100% |
10431
124.0 IPS |
|
|
Face Detection (I8)
|
89% |
8343
99.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
23744
184.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
23727
184.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
17757
137.7 IPS |
|
|
Style Transfer (F32)
|
100% |
79442
104.5 IPS |
|
|
Style Transfer (F16)
|
100% |
78014
102.6 IPS |
|
|
Style Transfer (I8)
|
98% |
64711
85.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
15427
550.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12999
464.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8311
296.8 IPS |
|
|
Text Classification (F32)
|
100% |
1362
1.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1522
2.19 KIPS |
|
|
Text Classification (I8)
|
98% |
817
1.17 KIPS |
|
|
Machine Translation (F32)
|
100% |
2970
54.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2952
54.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1429
26.3 IPS |
