Samsung Galaxy Z Flip5
Geekbench AI Score
912
Single Precision Score
774
Half Precision Score
1326
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 13 2025 03:04 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Flip5 |
| Model ID | samsung SM-F731N |
| 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% |
1083
201.3 IPS |
|
|
Image Classification (HP)
|
100% |
678
126.0 IPS |
|
|
Image Classification (Q)
|
100% |
1339
249.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
767
12.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
587
9.51 IPS |
|
|
Image Segmentation (Q)
|
98% |
1764
28.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2015
2.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
1501
1.75 IPS |
|
|
Pose Estimation (Q)
|
84% |
2839
3.37 IPS |
|
|
Object Detection (SP)
|
98% |
556
44.2 IPS |
|
|
Object Detection (HP)
|
98% |
313
24.9 IPS |
|
|
Object Detection (Q)
|
83% |
772
62.4 IPS |
|
|
Face Detection (SP)
|
100% |
1068
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1004
11.9 IPS |
|
|
Face Detection (Q)
|
95% |
1637
19.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
1235
9.54 IPS |
|
|
Depth Estimation (HP)
|
99% |
1366
10.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
1851
17.0 IPS |
|
|
Style Transfer (SP)
|
89% |
2875
3.73 IPS |
|
|
Style Transfer (HP)
|
89% |
1981
2.57 IPS |
|
|
Style Transfer (Q)
|
98% |
4991
6.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
644
23.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
749
27.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1467
54.4 IPS |
|
|
Text Classification (SP)
|
100% |
291
388.8 IPS |
|
|
Text Classification (HP)
|
99% |
244
325.7 IPS |
|
|
Text Classification (Q)
|
88% |
392
528.3 IPS |
|
|
Machine Translation (SP)
|
100% |
607
10.4 IPS |
|
|
Machine Translation (HP)
|
100% |
836
14.4 IPS |
|
|
Machine Translation (Q)
|
50% |
374
13.3 IPS |
