Samsung Galaxy S23 FE
Geekbench AI Score
966
Single Precision Score
1809
Half Precision Score
1405
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 17 2026 06:27 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S23 FE |
| Model ID | samsung SM-S711B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
622
115.7 IPS |
|
|
Image Classification (HP)
|
100% |
1170
217.6 IPS |
|
|
Image Classification (Q)
|
100% |
834
155.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
643
10.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1166
18.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1100
17.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3923
4.58 IPS |
|
|
Pose Estimation (HP)
|
99% |
8920
10.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
8849
10.4 IPS |
|
|
Object Detection (SP)
|
100% |
451
35.8 IPS |
|
|
Object Detection (HP)
|
99% |
835
66.3 IPS |
|
|
Object Detection (Q)
|
85% |
710
57.2 IPS |
|
|
Face Detection (SP)
|
100% |
2071
24.6 IPS |
|
|
Face Detection (HP)
|
100% |
3842
45.7 IPS |
|
|
Face Detection (Q)
|
97% |
2849
34.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2886
22.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
4778
36.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
3583
35.4 IPS |
|
|
Style Transfer (SP)
|
100% |
8008
10.3 IPS |
|
|
Style Transfer (HP)
|
100% |
15871
20.4 IPS |
|
|
Style Transfer (Q)
|
98% |
15319
19.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1252
46.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2638
97.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2517
93.3 IPS |
|
|
Text Classification (SP)
|
29% |
28
488.8 IPS |
|
|
Text Classification (HP)
|
35% |
57
517.8 IPS |
|
|
Text Classification (Q)
|
33% |
42
475.5 IPS |
|
|
Machine Translation (SP)
|
100% |
600
10.3 IPS |
|
|
Machine Translation (HP)
|
100% |
847
14.6 IPS |
|
|
Machine Translation (Q)
|
48% |
316
12.1 IPS |
