Samsung Galaxy Z Fold4
Geekbench ML Score
454
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:32 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 | 10.99 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
201
37.7 IPS |
|
|
Image Classification (F16)
|
100% |
197
36.8 IPS |
|
|
Image Classification (I8)
|
97% |
575
107.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
243
4.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
241
4.03 IPS |
|
|
Image Segmentation (I8)
|
98% |
587
9.81 IPS |
|
|
Pose Estimation (F32)
|
100% |
316
0.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
316
0.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
1362
1.65 IPS |
|
|
Object Detection (F32)
|
100% |
203
15.1 IPS |
|
|
Object Detection (F16)
|
100% |
201
15.0 IPS |
|
|
Object Detection (I8)
|
61% |
630
47.0 IPS |
|
|
Face Detection (F32)
|
100% |
519
6.17 IPS |
|
|
Face Detection (F16)
|
100% |
513
6.10 IPS |
|
|
Face Detection (I8)
|
86% |
1317
15.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
418
3.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
422
3.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
1332
10.3 IPS |
|
|
Style Transfer (F32)
|
100% |
715
0.94 IPS |
|
|
Style Transfer (F16)
|
100% |
719
0.95 IPS |
|
|
Style Transfer (I8)
|
98% |
1928
2.54 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
217
7.76 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
219
7.83 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
861
30.8 IPS |
|
|
Text Classification (F32)
|
100% |
286
410.7 IPS |
|
|
Text Classification (F16)
|
100% |
285
409.3 IPS |
|
|
Text Classification (I8)
|
92% |
519
746.1 IPS |
|
|
Machine Translation (F32)
|
100% |
475
8.74 IPS |
|
|
Machine Translation (F16)
|
100% |
461
8.48 IPS |
|
|
Machine Translation (I8)
|
64% |
619
11.4 IPS |
