Samsung Galaxy Z Fold4
Geekbench ML Score
436
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 06:37 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% |
171
31.9 IPS |
|
|
Image Classification (F16)
|
100% |
171
31.9 IPS |
|
|
Image Classification (I8)
|
97% |
464
86.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
237
3.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
252
4.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
600
10.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
365
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
358
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1380
1.67 IPS |
|
|
Object Detection (F32)
|
100% |
203
15.1 IPS |
|
|
Object Detection (F16)
|
100% |
203
15.1 IPS |
|
|
Object Detection (I8)
|
61% |
591
44.1 IPS |
|
|
Face Detection (F32)
|
100% |
537
6.38 IPS |
|
|
Face Detection (F16)
|
100% |
548
6.52 IPS |
|
|
Face Detection (I8)
|
86% |
1387
16.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
452
3.51 IPS |
|
|
Depth Estimation (F16)
|
100% |
444
3.45 IPS |
|
|
Depth Estimation (I8)
|
95% |
1302
10.1 IPS |
|
|
Style Transfer (F32)
|
100% |
705
0.93 IPS |
|
|
Style Transfer (F16)
|
100% |
704
0.93 IPS |
|
|
Style Transfer (I8)
|
98% |
1792
2.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
194
6.93 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
194
6.94 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
724
25.9 IPS |
|
|
Text Classification (F32)
|
100% |
231
331.8 IPS |
|
|
Text Classification (F16)
|
100% |
231
332.2 IPS |
|
|
Text Classification (I8)
|
92% |
422
606.2 IPS |
|
|
Machine Translation (F32)
|
100% |
475
8.74 IPS |
|
|
Machine Translation (F16)
|
100% |
476
8.77 IPS |
|
|
Machine Translation (I8)
|
64% |
548
10.1 IPS |
