Samsung Galaxy Z Fold4
Geekbench ML Score
700
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:26 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 | 10.99 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
370
69.3 IPS |
|
|
Image Classification (F16)
|
100% |
385
72.1 IPS |
|
|
Image Classification (I8)
|
97% |
544
101.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
441
7.37 IPS |
|
|
Image Segmentation (F16)
|
100% |
439
7.33 IPS |
|
|
Image Segmentation (I8)
|
98% |
538
8.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
798
0.97 IPS |
|
|
Pose Estimation (F16)
|
100% |
664
0.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
3330
4.03 IPS |
|
|
Object Detection (F32)
|
100% |
330
24.7 IPS |
|
|
Object Detection (F16)
|
100% |
336
25.1 IPS |
|
|
Object Detection (I8)
|
61% |
842
62.9 IPS |
|
|
Face Detection (F32)
|
100% |
711
8.46 IPS |
|
|
Face Detection (F16)
|
100% |
754
8.96 IPS |
|
|
Face Detection (I8)
|
86% |
1151
13.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
836
6.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
775
6.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
1501
11.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1517
2.00 IPS |
|
|
Style Transfer (F16)
|
100% |
1506
1.98 IPS |
|
|
Style Transfer (I8)
|
98% |
3284
4.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
501
17.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
506
18.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1426
50.9 IPS |
|
|
Text Classification (F32)
|
100% |
501
719.4 IPS |
|
|
Text Classification (F16)
|
100% |
424
609.8 IPS |
|
|
Text Classification (I8)
|
92% |
362
520.6 IPS |
|
|
Machine Translation (F32)
|
100% |
662
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
663
12.2 IPS |
|
|
Machine Translation (I8)
|
64% |
318
5.86 IPS |
