Samsung Galaxy Z Flip5
Geekbench AI Score
314
Single Precision Score
319
Half Precision Score
675
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | ChrisCR8IV |
| Upload Date | August 28 2024 03:02 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Flip5 |
| Model ID | samsung SM-F731U1 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 6.99 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
197
36.6 IPS |
|
|
Image Classification (HP)
|
100% |
199
37.0 IPS |
|
|
Image Classification (Q)
|
97% |
440
82.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
238
3.86 IPS |
|
|
Image Segmentation (HP)
|
100% |
242
3.92 IPS |
|
|
Image Segmentation (Q)
|
98% |
465
7.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
340
0.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
319
0.37 IPS |
|
|
Pose Estimation (Q)
|
98% |
1212
1.42 IPS |
|
|
Object Detection (SP)
|
100% |
182
14.5 IPS |
|
|
Object Detection (HP)
|
100% |
169
13.4 IPS |
|
|
Object Detection (Q)
|
89% |
556
44.5 IPS |
|
|
Face Detection (SP)
|
100% |
498
5.91 IPS |
|
|
Face Detection (HP)
|
100% |
512
6.08 IPS |
|
|
Face Detection (Q)
|
97% |
947
11.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
414
3.19 IPS |
|
|
Depth Estimation (HP)
|
100% |
407
3.14 IPS |
|
|
Depth Estimation (Q)
|
73% |
1171
9.58 IPS |
|
|
Style Transfer (SP)
|
100% |
670
0.86 IPS |
|
|
Style Transfer (HP)
|
100% |
680
0.87 IPS |
|
|
Style Transfer (Q)
|
98% |
1596
2.06 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
200
7.38 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
208
7.68 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
687
25.5 IPS |
|
|
Text Classification (SP)
|
100% |
255
340.9 IPS |
|
|
Text Classification (HP)
|
100% |
315
420.0 IPS |
|
|
Text Classification (Q)
|
91% |
370
497.6 IPS |
|
|
Machine Translation (SP)
|
100% |
457
7.87 IPS |
|
|
Machine Translation (HP)
|
100% |
456
7.86 IPS |
|
|
Machine Translation (Q)
|
57% |
320
7.81 IPS |
