Samsung Galaxy Z Fold4
Geekbench ML Score
480
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:28 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Fold4 |
| Model ID | samsung SM-F936B |
| 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 | 11.00 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
210
39.2 IPS |
|
|
Image Classification (F16)
|
100% |
210
39.2 IPS |
|
|
Image Classification (I8)
|
97% |
583
109.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
264
4.41 IPS |
|
|
Image Segmentation (F16)
|
100% |
264
4.41 IPS |
|
|
Image Segmentation (I8)
|
98% |
617
10.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
343
0.41 IPS |
|
|
Pose Estimation (F16)
|
100% |
339
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1464
1.77 IPS |
|
|
Object Detection (F32)
|
100% |
217
16.2 IPS |
|
|
Object Detection (F16)
|
100% |
216
16.2 IPS |
|
|
Object Detection (I8)
|
61% |
634
47.4 IPS |
|
|
Face Detection (F32)
|
100% |
571
6.78 IPS |
|
|
Face Detection (F16)
|
100% |
562
6.68 IPS |
|
|
Face Detection (I8)
|
86% |
1395
16.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
461
3.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
465
3.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
1403
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
762
1.00 IPS |
|
|
Style Transfer (F16)
|
100% |
759
1.00 IPS |
|
|
Style Transfer (I8)
|
98% |
2031
2.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
228
8.14 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
232
8.28 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
894
31.9 IPS |
|
|
Text Classification (F32)
|
100% |
286
410.7 IPS |
|
|
Text Classification (F16)
|
100% |
286
410.3 IPS |
|
|
Text Classification (I8)
|
92% |
519
745.7 IPS |
|
|
Machine Translation (F32)
|
100% |
497
9.15 IPS |
|
|
Machine Translation (F16)
|
100% |
492
9.05 IPS |
|
|
Machine Translation (I8)
|
64% |
634
11.7 IPS |
