Micro-Star International Co., Ltd. MS-7C37
Geekbench ML Score
11738
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 11:50 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7C37 |
| Motherboard | Micro-Star International Co., Ltd. X570-A PRO (MS-7C37) |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5800X3D |
| 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 | 96.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon RX 6750 XT |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7660
1.43 KIPS |
|
|
Image Classification (F16)
|
100% |
7503
1.40 KIPS |
|
|
Image Classification (I8)
|
100% |
6808
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
7631
127.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
6778
113.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
7206
120.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
119854
145.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
119930
145.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
100946
122.2 IPS |
|
|
Object Detection (F32)
|
100% |
3096
231.1 IPS |
|
|
Object Detection (F16)
|
100% |
3041
227.0 IPS |
|
|
Object Detection (I8)
|
62% |
3089
230.6 IPS |
|
|
Face Detection (F32)
|
100% |
23488
279.3 IPS |
|
|
Face Detection (F16)
|
100% |
23008
273.6 IPS |
|
|
Face Detection (I8)
|
89% |
18027
214.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
28504
221.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
29503
228.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
23184
179.8 IPS |
|
|
Style Transfer (F32)
|
100% |
108376
142.6 IPS |
|
|
Style Transfer (F16)
|
100% |
105883
139.3 IPS |
|
|
Style Transfer (I8)
|
98% |
93572
123.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9141
326.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
9146
326.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8529
304.6 IPS |
|
|
Text Classification (F32)
|
100% |
2180
3.13 KIPS |
|
|
Text Classification (F16)
|
100% |
2154
3.10 KIPS |
|
|
Text Classification (I8)
|
98% |
1677
2.41 KIPS |
|
|
Machine Translation (F32)
|
100% |
2791
51.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2678
49.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2324
42.8 IPS |
