Micro-Star International Co., Ltd. B450 Gaming MAG META 5 (MS-B930)
Geekbench ML Score
8894
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | December 22 2023 12:33 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Enterprise LTSC (64-bit) |
| Model | Micro-Star International Co., Ltd. B450 Gaming MAG META 5 (MS-B930) |
| Motherboard | Micro-Star International Co., Ltd. B450M PRO-VDH MAX (MS-7A38) |
| Power Plan | WinterOS: Rev10 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 3700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 23 Model 113 Stepping 0 |
| Base Frequency | 3.60 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 | 16.0 MB x 2 |
| Memory Information | |
|---|---|
| Size | 40.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 2060 SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5007
936.9 IPS |
|
|
Image Classification (F16)
|
100% |
5003
936.1 IPS |
|
|
Image Classification (I8)
|
100% |
3800
711.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
5703
95.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
5713
95.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
4870
81.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
46030
55.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
50811
61.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
50703
61.4 IPS |
|
|
Object Detection (F32)
|
100% |
3320
247.9 IPS |
|
|
Object Detection (F16)
|
100% |
3194
238.4 IPS |
|
|
Object Detection (I8)
|
61% |
2891
215.9 IPS |
|
|
Face Detection (F32)
|
100% |
12677
150.7 IPS |
|
|
Face Detection (F16)
|
100% |
12695
150.9 IPS |
|
|
Face Detection (I8)
|
89% |
10201
121.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
27112
210.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
26203
203.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
22818
177.0 IPS |
|
|
Style Transfer (F32)
|
100% |
84359
111.0 IPS |
|
|
Style Transfer (F16)
|
100% |
84929
111.7 IPS |
|
|
Style Transfer (I8)
|
98% |
71417
93.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
15137
540.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15232
544.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
9658
344.9 IPS |
|
|
Text Classification (F32)
|
100% |
1450
2.08 KIPS |
|
|
Text Classification (F16)
|
100% |
1733
2.49 KIPS |
|
|
Text Classification (I8)
|
98% |
1108
1.59 KIPS |
|
|
Machine Translation (F32)
|
100% |
2223
40.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2239
41.2 IPS |
|
|
Machine Translation (I8)
|
70% |
1292
23.8 IPS |
