Micro-Star International Co., Ltd. MS-7C95
Geekbench ML Score
8175
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 03:08 PM |
| Views | 3 |
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% |
4018
751.9 IPS |
|
|
Image Classification (F16)
|
100% |
4013
750.9 IPS |
|
|
Image Classification (I8)
|
100% |
3141
587.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
6875
114.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
6089
101.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
5044
84.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
39837
48.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
46558
56.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
40066
48.5 IPS |
|
|
Object Detection (F32)
|
100% |
3566
266.2 IPS |
|
|
Object Detection (F16)
|
100% |
3151
235.2 IPS |
|
|
Object Detection (I8)
|
60% |
2682
200.2 IPS |
|
|
Face Detection (F32)
|
100% |
10559
125.6 IPS |
|
|
Face Detection (F16)
|
100% |
10556
125.5 IPS |
|
|
Face Detection (I8)
|
89% |
8351
99.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
23902
185.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
23890
185.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
17830
138.3 IPS |
|
|
Style Transfer (F32)
|
100% |
79409
104.5 IPS |
|
|
Style Transfer (F16)
|
100% |
79285
104.3 IPS |
|
|
Style Transfer (I8)
|
98% |
65399
86.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12676
452.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13081
467.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8304
296.6 IPS |
|
|
Text Classification (F32)
|
100% |
1366
1.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1370
1.97 KIPS |
|
|
Text Classification (I8)
|
98% |
795
1.14 KIPS |
|
|
Machine Translation (F32)
|
100% |
2947
54.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2952
54.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1424
26.2 IPS |
