Samsung Galaxy Z Flip4
Geekbench ML Score
478
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 05:05 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Flip4 |
| Model ID | samsung SM-F721B |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Cluster 2 | 3 Cores @ 2.75 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
208
38.9 IPS |
|
|
Image Classification (F16)
|
100% |
208
38.8 IPS |
|
|
Image Classification (I8)
|
97% |
580
108.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
261
4.36 IPS |
|
|
Image Segmentation (F16)
|
100% |
261
4.36 IPS |
|
|
Image Segmentation (I8)
|
98% |
611
10.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1431
1.73 IPS |
|
|
Object Detection (F32)
|
100% |
215
16.1 IPS |
|
|
Object Detection (F16)
|
100% |
216
16.1 IPS |
|
|
Object Detection (I8)
|
61% |
632
47.2 IPS |
|
|
Face Detection (F32)
|
100% |
553
6.57 IPS |
|
|
Face Detection (F16)
|
100% |
554
6.58 IPS |
|
|
Face Detection (I8)
|
86% |
1375
16.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
457
3.54 IPS |
|
|
Depth Estimation (F16)
|
100% |
456
3.53 IPS |
|
|
Depth Estimation (I8)
|
95% |
1377
10.7 IPS |
|
|
Style Transfer (F32)
|
100% |
763
1.00 IPS |
|
|
Style Transfer (F16)
|
100% |
763
1.00 IPS |
|
|
Style Transfer (I8)
|
98% |
1970
2.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
234
8.37 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
234
8.35 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
896
32.0 IPS |
|
|
Text Classification (F32)
|
100% |
286
410.5 IPS |
|
|
Text Classification (F16)
|
100% |
286
410.8 IPS |
|
|
Text Classification (I8)
|
92% |
520
747.3 IPS |
|
|
Machine Translation (F32)
|
100% |
495
9.12 IPS |
|
|
Machine Translation (F16)
|
100% |
495
9.10 IPS |
|
|
Machine Translation (I8)
|
64% |
632
11.6 IPS |
