Samsung Galaxy S23
Geekbench AI Score
1479
Single Precision Score
1426
Half Precision Score
2034
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 18 2025 05:00 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| 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 | 6.91 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1823
339.0 IPS |
|
|
Image Classification (HP)
|
100% |
1638
304.6 IPS |
|
|
Image Classification (Q)
|
100% |
2503
465.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1769
28.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1715
27.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2556
41.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2571
3.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
2439
2.85 IPS |
|
|
Pose Estimation (Q)
|
84% |
3970
4.71 IPS |
|
|
Object Detection (SP)
|
98% |
935
74.4 IPS |
|
|
Object Detection (HP)
|
98% |
759
60.4 IPS |
|
|
Object Detection (Q)
|
83% |
1061
85.7 IPS |
|
|
Face Detection (SP)
|
100% |
1870
22.2 IPS |
|
|
Face Detection (HP)
|
100% |
1920
22.8 IPS |
|
|
Face Detection (Q)
|
95% |
2843
33.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
1826
14.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1833
14.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2866
26.3 IPS |
|
|
Style Transfer (SP)
|
89% |
4542
5.90 IPS |
|
|
Style Transfer (HP)
|
89% |
4539
5.89 IPS |
|
|
Style Transfer (Q)
|
98% |
7799
10.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
976
36.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
969
35.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2015
74.7 IPS |
|
|
Text Classification (SP)
|
100% |
410
547.4 IPS |
|
|
Text Classification (HP)
|
99% |
448
598.2 IPS |
|
|
Text Classification (Q)
|
88% |
694
936.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1042
18.0 IPS |
|
|
Machine Translation (HP)
|
100% |
965
16.6 IPS |
|
|
Machine Translation (Q)
|
50% |
507
18.0 IPS |
