Micro-Star International Co., Ltd. MEG Z490 Infinite X (MS-B916)
Geekbench ML Score
7562
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | arnes |
| Upload Date | August 16 2024 11:25 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. MEG Z490 Infinite X (MS-B916) |
| Motherboard | Micro-Star International Co., Ltd. Z490M-S01 (MS-7C99) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10700KF |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 256 KB x 8 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 48.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 2070 SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5486
1.03 KIPS |
|
|
Image Classification (F16)
|
100% |
5462
1.02 KIPS |
|
|
Image Classification (I8)
|
100% |
4085
764.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
7319
122.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
7392
123.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
6102
101.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
61166
74.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
55241
66.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
46613
56.4 IPS |
|
|
Object Detection (F32)
|
100% |
2743
204.7 IPS |
|
|
Object Detection (F16)
|
100% |
2661
198.6 IPS |
|
|
Object Detection (I8)
|
61% |
2321
173.2 IPS |
|
|
Face Detection (F32)
|
100% |
14613
173.8 IPS |
|
|
Face Detection (F16)
|
100% |
14487
172.2 IPS |
|
|
Face Detection (I8)
|
89% |
11329
134.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
27206
211.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
31874
247.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
16829
130.5 IPS |
|
|
Style Transfer (F32)
|
100% |
33617
44.2 IPS |
|
|
Style Transfer (F16)
|
100% |
87715
115.4 IPS |
|
|
Style Transfer (I8)
|
98% |
75835
99.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12206
435.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12401
442.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
8582
306.5 IPS |
|
|
Text Classification (F32)
|
100% |
645
927.6 IPS |
|
|
Text Classification (F16)
|
100% |
649
933.0 IPS |
|
|
Text Classification (I8)
|
98% |
476
683.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1108
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1106
20.3 IPS |
|
|
Machine Translation (I8)
|
70% |
856
15.8 IPS |
