Micro-Star International Co., Ltd. MS-7D91
Geekbench ML Score
26279
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 17 2024 01:10 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D91 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z790 EDGE WIFI (MS-7D91) |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700K |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 2.00 MB x 3 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
12243
2.29 KIPS |
|
|
Image Classification (F16)
|
100% |
12719
2.38 KIPS |
|
|
Image Classification (I8)
|
100% |
10836
2.03 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17528
292.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
17642
294.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
16309
272.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
242645
293.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
242766
294.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
214687
260.0 IPS |
|
|
Object Detection (F32)
|
100% |
7592
566.8 IPS |
|
|
Object Detection (F16)
|
100% |
7691
574.2 IPS |
|
|
Object Detection (I8)
|
56% |
7168
535.1 IPS |
|
|
Face Detection (F32)
|
100% |
38932
462.9 IPS |
|
|
Face Detection (F16)
|
100% |
38604
459.0 IPS |
|
|
Face Detection (I8)
|
89% |
34358
408.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
75255
583.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
69898
542.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
54968
426.3 IPS |
|
|
Style Transfer (F32)
|
100% |
353984
465.6 IPS |
|
|
Style Transfer (F16)
|
100% |
348665
458.6 IPS |
|
|
Style Transfer (I8)
|
98% |
311820
410.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
49861
1.78 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
46553
1.66 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
39510
1.41 KIPS |
|
|
Text Classification (F32)
|
100% |
3492
5.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3453
4.96 KIPS |
|
|
Text Classification (I8)
|
98% |
2083
2.99 KIPS |
|
|
Machine Translation (F32)
|
100% |
4850
89.3 IPS |
|
|
Machine Translation (F16)
|
100% |
4769
87.8 IPS |
|
|
Machine Translation (I8)
|
70% |
2812
51.7 IPS |
