Gigabyte Technology Co., Ltd. H97N-WIFI
Geekbench ML Score
207
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | August 16 2024 09:26 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Linux Mint 22 |
| Model | Gigabyte Technology Co., Ltd. H97N-WIFI |
| Motherboard | Gigabyte Technology Co., Ltd. H97N-WIFI |
| CPU Information | |
|---|---|
| Name | Intel Core i5-4590S |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 15.49 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
63
11.9 IPS |
|
|
Image Classification (F16)
|
100% |
646
120.9 IPS |
|
|
Image Classification (I8)
|
99% |
56
10.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
227
3.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
154
2.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
141
2.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
598
0.72 IPS |
|
|
Pose Estimation (F16)
|
100% |
592
0.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
449
0.54 IPS |
|
|
Object Detection (F32)
|
100% |
100
7.45 IPS |
|
|
Object Detection (F16)
|
100% |
105
7.86 IPS |
|
|
Object Detection (I8)
|
65% |
99
7.39 IPS |
|
|
Face Detection (F32)
|
100% |
256
3.05 IPS |
|
|
Face Detection (F16)
|
100% |
278
3.31 IPS |
|
|
Face Detection (I8)
|
87% |
230
2.73 IPS |
|
|
Depth Estimation (F32)
|
100% |
334
2.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
1048
8.13 IPS |
|
|
Depth Estimation (I8)
|
95% |
255
1.98 IPS |
|
|
Style Transfer (F32)
|
100% |
967
1.27 IPS |
|
|
Style Transfer (F16)
|
100% |
979
1.29 IPS |
|
|
Style Transfer (I8)
|
98% |
1019
1.34 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
147
5.24 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
154
5.49 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
152
5.43 IPS |
|
|
Text Classification (F32)
|
100% |
123
176.1 IPS |
|
|
Text Classification (F16)
|
100% |
171
246.3 IPS |
|
|
Text Classification (I8)
|
92% |
20
29.3 IPS |
|
|
Machine Translation (F32)
|
100% |
93
1.72 IPS |
|
|
Machine Translation (F16)
|
100% |
178
3.28 IPS |
|
|
Machine Translation (I8)
|
62% |
52
0.96 IPS |
