Samsung Galaxy Z Fold4
Geekbench ML Score
457
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:57 PM |
| Views | 1 |
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% |
186
34.8 IPS |
|
|
Image Classification (F16)
|
100% |
197
36.9 IPS |
|
|
Image Classification (I8)
|
97% |
564
105.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
248
4.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
248
4.14 IPS |
|
|
Image Segmentation (I8)
|
98% |
589
9.84 IPS |
|
|
Pose Estimation (F32)
|
100% |
350
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
313
0.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
1410
1.71 IPS |
|
|
Object Detection (F32)
|
100% |
145
10.8 IPS |
|
|
Object Detection (F16)
|
100% |
213
15.9 IPS |
|
|
Object Detection (I8)
|
61% |
635
47.4 IPS |
|
|
Face Detection (F32)
|
100% |
546
6.49 IPS |
|
|
Face Detection (F16)
|
100% |
533
6.34 IPS |
|
|
Face Detection (I8)
|
86% |
1365
16.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
445
3.45 IPS |
|
|
Depth Estimation (F16)
|
100% |
448
3.47 IPS |
|
|
Depth Estimation (I8)
|
95% |
1346
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
733
0.96 IPS |
|
|
Style Transfer (F16)
|
100% |
731
0.96 IPS |
|
|
Style Transfer (I8)
|
98% |
1990
2.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
220
7.85 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
222
7.91 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
852
30.4 IPS |
|
|
Text Classification (F32)
|
100% |
286
411.1 IPS |
|
|
Text Classification (F16)
|
100% |
287
412.8 IPS |
|
|
Text Classification (I8)
|
92% |
519
746.1 IPS |
|
|
Machine Translation (F32)
|
100% |
478
8.80 IPS |
|
|
Machine Translation (F16)
|
100% |
473
8.70 IPS |
|
|
Machine Translation (I8)
|
64% |
613
11.3 IPS |
