Samsung Galaxy S23 Ultra
Geekbench AI Score
772
Single Precision Score
837
Half Precision Score
1350
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 06:47 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918B |
| 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 | 10.79 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
593
110.4 IPS |
|
|
Image Classification (HP)
|
100% |
694
129.1 IPS |
|
|
Image Classification (Q)
|
100% |
1363
253.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
664
10.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
635
10.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
975
15.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1426
1.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
1411
1.65 IPS |
|
|
Pose Estimation (Q)
|
84% |
2878
3.41 IPS |
|
|
Object Detection (SP)
|
98% |
317
25.2 IPS |
|
|
Object Detection (HP)
|
98% |
556
44.2 IPS |
|
|
Object Detection (Q)
|
83% |
788
63.7 IPS |
|
|
Face Detection (SP)
|
100% |
973
11.6 IPS |
|
|
Face Detection (HP)
|
100% |
969
11.5 IPS |
|
|
Face Detection (Q)
|
95% |
2097
25.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
966
7.46 IPS |
|
|
Depth Estimation (HP)
|
99% |
869
6.72 IPS |
|
|
Depth Estimation (Q)
|
64% |
2416
22.1 IPS |
|
|
Style Transfer (SP)
|
89% |
2921
3.79 IPS |
|
|
Style Transfer (HP)
|
89% |
2918
3.79 IPS |
|
|
Style Transfer (Q)
|
98% |
4514
5.82 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
659
24.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
671
24.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1475
54.7 IPS |
|
|
Text Classification (SP)
|
100% |
348
463.9 IPS |
|
|
Text Classification (HP)
|
99% |
345
461.0 IPS |
|
|
Text Classification (Q)
|
88% |
494
665.7 IPS |
|
|
Machine Translation (SP)
|
100% |
679
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
861
14.8 IPS |
|
|
Machine Translation (Q)
|
50% |
403
14.3 IPS |
