Samsung Galaxy Z Fold4
Geekbench AI Score
1954
Single Precision Score
1912
Half Precision Score
3015
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 25 2024 10:04 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8+ Gen 1 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Fold4 |
| Model ID | samsung SM-F936U |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1631
303.2 IPS |
|
|
Image Classification (HP)
|
100% |
1635
304.0 IPS |
|
|
Image Classification (Q)
|
100% |
2340
435.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1622
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1621
26.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2619
42.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2731
3.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
2647
3.09 IPS |
|
|
Pose Estimation (Q)
|
84% |
5968
7.08 IPS |
|
|
Object Detection (SP)
|
98% |
1466
116.6 IPS |
|
|
Object Detection (HP)
|
98% |
1476
117.4 IPS |
|
|
Object Detection (Q)
|
83% |
2061
166.5 IPS |
|
|
Face Detection (SP)
|
100% |
2687
31.9 IPS |
|
|
Face Detection (HP)
|
100% |
2421
28.8 IPS |
|
|
Face Detection (Q)
|
95% |
5042
60.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
2965
22.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2908
22.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
5131
47.0 IPS |
|
|
Style Transfer (SP)
|
89% |
6209
8.06 IPS |
|
|
Style Transfer (HP)
|
89% |
6114
7.94 IPS |
|
|
Style Transfer (Q)
|
98% |
12382
16.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1509
55.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1481
54.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3220
119.3 IPS |
|
|
Text Classification (SP)
|
100% |
741
988.8 IPS |
|
|
Text Classification (HP)
|
99% |
748
998.8 IPS |
|
|
Text Classification (Q)
|
88% |
1221
1.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
1387
23.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1328
22.9 IPS |
|
|
Machine Translation (Q)
|
50% |
654
23.2 IPS |
