Micro-Star International Co., Ltd. MS-7E06
Geekbench ML Score
22607
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 17 2024 05:08 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E06 |
| Motherboard | Micro-Star International Co., Ltd. PRO Z790-P DDR4 (MS-7E06) |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600KF |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
11210
2.10 KIPS |
|
|
Image Classification (F16)
|
100% |
11399
2.13 KIPS |
|
|
Image Classification (I8)
|
100% |
10208
1.91 KIPS |
|
|
Image Segmentation (F32)
|
100% |
15850
264.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
15591
260.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
14169
236.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
154828
187.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
155689
188.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
139846
169.3 IPS |
|
|
Object Detection (F32)
|
100% |
6775
505.8 IPS |
|
|
Object Detection (F16)
|
100% |
6828
509.8 IPS |
|
|
Object Detection (I8)
|
63% |
6280
468.8 IPS |
|
|
Face Detection (F32)
|
100% |
31330
372.5 IPS |
|
|
Face Detection (F16)
|
100% |
33083
393.4 IPS |
|
|
Face Detection (I8)
|
89% |
27458
326.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
67282
521.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
58408
453.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
48577
376.7 IPS |
|
|
Style Transfer (F32)
|
100% |
267509
351.9 IPS |
|
|
Style Transfer (F16)
|
100% |
269568
354.6 IPS |
|
|
Style Transfer (I8)
|
98% |
242532
319.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
45867
1.64 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
46112
1.65 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33048
1.18 KIPS |
|
|
Text Classification (F32)
|
100% |
3447
4.95 KIPS |
|
|
Text Classification (F16)
|
100% |
3471
4.99 KIPS |
|
|
Text Classification (I8)
|
98% |
2071
2.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
4623
85.1 IPS |
|
|
Machine Translation (F16)
|
100% |
4561
83.9 IPS |
|
|
Machine Translation (I8)
|
70% |
2732
50.3 IPS |
