Micro-Star International Co., Ltd. MS-7D78
Geekbench ML Score
16896
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | May 07 2024 12:00 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D78 |
| Motherboard | Micro-Star International Co., Ltd. PRO B650-P WIFI (MS-7D78) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 7700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 4.50 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 1.00 MB x 8 |
| L3 Cache | 32.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4060 Ti |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7706
1.44 KIPS |
|
|
Image Classification (F16)
|
100% |
8493
1.59 KIPS |
|
|
Image Classification (I8)
|
100% |
7451
1.39 KIPS |
|
|
Image Segmentation (F32)
|
100% |
12658
211.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
11806
197.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
11771
196.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
107686
130.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
107244
129.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
94816
114.8 IPS |
|
|
Object Detection (F32)
|
100% |
6190
462.1 IPS |
|
|
Object Detection (F16)
|
100% |
6284
469.2 IPS |
|
|
Object Detection (I8)
|
63% |
5641
421.2 IPS |
|
|
Face Detection (F32)
|
100% |
21725
258.3 IPS |
|
|
Face Detection (F16)
|
100% |
21538
256.1 IPS |
|
|
Face Detection (I8)
|
89% |
18089
215.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
46495
360.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
47323
367.0 IPS |
|
|
Depth Estimation (I8)
|
94% |
34053
264.1 IPS |
|
|
Style Transfer (F32)
|
100% |
191033
251.3 IPS |
|
|
Style Transfer (F16)
|
100% |
184972
243.3 IPS |
|
|
Style Transfer (I8)
|
98% |
161483
212.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
31251
1.12 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
31708
1.13 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
23162
827.2 IPS |
|
|
Text Classification (F32)
|
100% |
2729
3.92 KIPS |
|
|
Text Classification (F16)
|
100% |
2623
3.77 KIPS |
|
|
Text Classification (I8)
|
98% |
1721
2.47 KIPS |
|
|
Machine Translation (F32)
|
100% |
3895
71.7 IPS |
|
|
Machine Translation (F16)
|
100% |
3864
71.1 IPS |
|
|
Machine Translation (I8)
|
70% |
2150
39.6 IPS |
