Samsung Galaxy Z Flip5
Geekbench AI Score
360
Single Precision Score
337
Half Precision Score
745
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | ChrisCR8IV |
| Upload Date | August 28 2024 02:49 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
314
58.5 IPS |
|
|
Image Classification (HP)
|
100% |
301
56.0 IPS |
|
|
Image Classification (Q)
|
97% |
765
142.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
387
6.27 IPS |
|
|
Image Segmentation (HP)
|
100% |
384
6.23 IPS |
|
|
Image Segmentation (Q)
|
98% |
781
12.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
521
0.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
318
0.37 IPS |
|
|
Pose Estimation (Q)
|
98% |
1284
1.50 IPS |
|
|
Object Detection (SP)
|
100% |
199
15.8 IPS |
|
|
Object Detection (HP)
|
100% |
185
14.7 IPS |
|
|
Object Detection (Q)
|
89% |
496
39.7 IPS |
|
|
Face Detection (SP)
|
100% |
466
5.54 IPS |
|
|
Face Detection (HP)
|
100% |
477
5.67 IPS |
|
|
Face Detection (Q)
|
97% |
1058
12.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
400
3.08 IPS |
|
|
Depth Estimation (HP)
|
100% |
391
3.01 IPS |
|
|
Depth Estimation (Q)
|
73% |
953
7.79 IPS |
|
|
Style Transfer (SP)
|
100% |
666
0.86 IPS |
|
|
Style Transfer (HP)
|
100% |
664
0.85 IPS |
|
|
Style Transfer (Q)
|
98% |
1500
1.93 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
207
7.65 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
202
7.46 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
673
24.9 IPS |
|
|
Text Classification (SP)
|
100% |
255
340.7 IPS |
|
|
Text Classification (HP)
|
100% |
257
342.8 IPS |
|
|
Text Classification (Q)
|
91% |
453
609.1 IPS |
|
|
Machine Translation (SP)
|
100% |
449
7.73 IPS |
|
|
Machine Translation (HP)
|
100% |
440
7.57 IPS |
|
|
Machine Translation (Q)
|
57% |
304
7.44 IPS |
