Samsung Galaxy S23 Ultra
Geekbench AI Score
1974
Single Precision Score
2030
Half Precision Score
3165
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 02 2025 03:18 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 10.77 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
884
164.4 IPS |
|
|
Image Classification (HP)
|
100% |
1377
256.1 IPS |
|
|
Image Classification (Q)
|
100% |
2225
413.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1695
27.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1491
24.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2462
40.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2723
3.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
3211
3.75 IPS |
|
|
Pose Estimation (Q)
|
84% |
7159
8.49 IPS |
|
|
Object Detection (SP)
|
98% |
1669
132.8 IPS |
|
|
Object Detection (HP)
|
98% |
1675
133.3 IPS |
|
|
Object Detection (Q)
|
83% |
2364
190.9 IPS |
|
|
Face Detection (SP)
|
100% |
3081
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
2770
32.9 IPS |
|
|
Face Detection (Q)
|
95% |
5280
63.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3251
25.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
2970
23.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
4331
39.7 IPS |
|
|
Style Transfer (SP)
|
89% |
7645
9.92 IPS |
|
|
Style Transfer (HP)
|
89% |
7651
9.93 IPS |
|
|
Style Transfer (Q)
|
98% |
14517
18.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1682
62.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1689
62.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3743
138.7 IPS |
|
|
Text Classification (SP)
|
100% |
693
925.3 IPS |
|
|
Text Classification (HP)
|
99% |
696
929.2 IPS |
|
|
Text Classification (Q)
|
88% |
1166
1.57 KIPS |
|
|
Machine Translation (SP)
|
100% |
1485
25.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1461
25.2 IPS |
|
|
Machine Translation (Q)
|
50% |
753
26.7 IPS |
