Samsung Galaxy S23 FE
Geekbench AI Score
1451
Single Precision Score
1426
Half Precision Score
2119
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 17 2026 06:22 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1351
251.3 IPS |
|
|
Image Classification (HP)
|
100% |
1337
248.6 IPS |
|
|
Image Classification (Q)
|
100% |
2068
384.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1355
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1232
20.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1972
32.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2310
2.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
2008
2.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
3734
4.43 IPS |
|
|
Object Detection (SP)
|
98% |
921
73.3 IPS |
|
|
Object Detection (HP)
|
98% |
1028
81.8 IPS |
|
|
Object Detection (Q)
|
83% |
1341
108.3 IPS |
|
|
Face Detection (SP)
|
100% |
1846
21.9 IPS |
|
|
Face Detection (HP)
|
100% |
1887
22.4 IPS |
|
|
Face Detection (Q)
|
95% |
3288
39.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2279
17.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2259
17.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
3347
30.7 IPS |
|
|
Style Transfer (SP)
|
89% |
4749
6.17 IPS |
|
|
Style Transfer (HP)
|
89% |
4697
6.10 IPS |
|
|
Style Transfer (Q)
|
98% |
8926
11.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1113
41.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1097
40.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2268
84.1 IPS |
|
|
Text Classification (SP)
|
100% |
458
611.3 IPS |
|
|
Text Classification (HP)
|
99% |
462
616.4 IPS |
|
|
Text Classification (Q)
|
88% |
826
1.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
1043
18.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1013
17.5 IPS |
|
|
Machine Translation (Q)
|
50% |
486
17.3 IPS |
