Micro-Star International Co., Ltd. MS-7C95
Geekbench ML Score
8276
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 02:47 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% |
4009
750.3 IPS |
|
|
Image Classification (F16)
|
100% |
4018
752.0 IPS |
|
|
Image Classification (I8)
|
100% |
3144
588.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
6908
115.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
6087
101.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
5065
84.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
37755
45.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
46888
56.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
40012
48.5 IPS |
|
|
Object Detection (F32)
|
100% |
3585
267.6 IPS |
|
|
Object Detection (F16)
|
100% |
3505
261.6 IPS |
|
|
Object Detection (I8)
|
60% |
3077
229.7 IPS |
|
|
Face Detection (F32)
|
100% |
10416
123.9 IPS |
|
|
Face Detection (F16)
|
100% |
10585
125.9 IPS |
|
|
Face Detection (I8)
|
89% |
8337
99.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
23922
185.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
19558
151.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
17835
138.3 IPS |
|
|
Style Transfer (F32)
|
100% |
79961
105.2 IPS |
|
|
Style Transfer (F16)
|
100% |
79581
104.7 IPS |
|
|
Style Transfer (I8)
|
98% |
65640
86.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13061
466.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12756
455.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8300
296.4 IPS |
|
|
Text Classification (F32)
|
100% |
1365
1.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1610
2.31 KIPS |
|
|
Text Classification (I8)
|
98% |
953
1.37 KIPS |
|
|
Machine Translation (F32)
|
100% |
2967
54.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2951
54.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1428
26.3 IPS |
