Samsung Galaxy S23
Geekbench AI Score
1306
Single Precision Score
1295
Half Precision Score
1810
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 12 2025 06:37 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% |
1495
278.0 IPS |
|
|
Image Classification (HP)
|
100% |
1424
264.8 IPS |
|
|
Image Classification (Q)
|
100% |
2232
415.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1578
25.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1479
24.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2285
37.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2436
2.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
2469
2.88 IPS |
|
|
Pose Estimation (Q)
|
84% |
3607
4.28 IPS |
|
|
Object Detection (SP)
|
98% |
843
67.1 IPS |
|
|
Object Detection (HP)
|
98% |
841
66.9 IPS |
|
|
Object Detection (Q)
|
83% |
1179
95.2 IPS |
|
|
Face Detection (SP)
|
100% |
1738
20.7 IPS |
|
|
Face Detection (HP)
|
100% |
1752
20.8 IPS |
|
|
Face Detection (Q)
|
95% |
2482
29.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
1675
12.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1716
13.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
2356
21.6 IPS |
|
|
Style Transfer (SP)
|
89% |
4121
5.35 IPS |
|
|
Style Transfer (HP)
|
89% |
4135
5.37 IPS |
|
|
Style Transfer (Q)
|
98% |
7169
9.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
868
32.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
871
32.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1801
66.7 IPS |
|
|
Text Classification (SP)
|
100% |
343
458.0 IPS |
|
|
Text Classification (HP)
|
99% |
338
450.5 IPS |
|
|
Text Classification (Q)
|
88% |
573
772.9 IPS |
|
|
Machine Translation (SP)
|
100% |
835
14.4 IPS |
|
|
Machine Translation (HP)
|
100% |
830
14.3 IPS |
|
|
Machine Translation (Q)
|
50% |
404
14.3 IPS |
