samsung SM-G970F
Geekbench ML Score
331
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 05:06 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-G970F |
| Model ID | samsung SM-G970F |
| Motherboard | exynos9820 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.31 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 5.29 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
163
30.6 IPS |
|
|
Image Classification (F16)
|
100% |
159
29.8 IPS |
|
|
Image Classification (I8)
|
97% |
353
66.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
240
4.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
274
4.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
381
6.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
1049
1.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
4188
5.07 IPS |
|
|
Pose Estimation (I8)
|
100% |
948
1.15 IPS |
|
|
Object Detection (F32)
|
100% |
166
12.4 IPS |
|
|
Object Detection (F16)
|
100% |
165
12.4 IPS |
|
|
Object Detection (I8)
|
61% |
385
28.7 IPS |
|
|
Face Detection (F32)
|
100% |
396
4.71 IPS |
|
|
Face Detection (F16)
|
100% |
394
4.68 IPS |
|
|
Face Detection (I8)
|
86% |
770
9.16 IPS |
|
|
Depth Estimation (F32)
|
100% |
356
2.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
357
2.76 IPS |
|
|
Depth Estimation (I8)
|
95% |
851
6.60 IPS |
|
|
Style Transfer (F32)
|
100% |
661
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
674
0.89 IPS |
|
|
Style Transfer (I8)
|
98% |
372
0.49 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
383
13.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
790
28.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
615
22.0 IPS |
|
|
Text Classification (F32)
|
100% |
27
38.2 IPS |
|
|
Text Classification (F16)
|
100% |
27
39.4 IPS |
|
|
Text Classification (I8)
|
92% |
23
33.1 IPS |
|
|
Machine Translation (F32)
|
100% |
392
7.21 IPS |
|
|
Machine Translation (F16)
|
100% |
376
6.92 IPS |
|
|
Machine Translation (I8)
|
64% |
408
7.52 IPS |
