Samsung Galaxy S24+
Geekbench AI Score
1204
Single Precision Score
1652
Half Precision Score
1549
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | LeVLBars |
| Upload Date | April 29 2025 05:27 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926U1 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
826
153.5 IPS |
|
|
Image Classification (HP)
|
100% |
720
133.8 IPS |
|
|
Image Classification (Q)
|
96% |
605
112.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1355
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1319
21.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1058
17.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1120
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2740
3.20 IPS |
|
|
Pose Estimation (Q)
|
96% |
2732
3.20 IPS |
|
|
Object Detection (SP)
|
100% |
676
53.6 IPS |
|
|
Object Detection (HP)
|
100% |
768
60.9 IPS |
|
|
Object Detection (Q)
|
87% |
793
63.6 IPS |
|
|
Face Detection (SP)
|
100% |
3040
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
3159
37.5 IPS |
|
|
Face Detection (Q)
|
97% |
2333
27.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1894
14.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
3967
30.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
3260
30.2 IPS |
|
|
Style Transfer (SP)
|
100% |
7402
9.51 IPS |
|
|
Style Transfer (HP)
|
100% |
11865
15.3 IPS |
|
|
Style Transfer (Q)
|
98% |
11765
15.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
545
20.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1579
58.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1406
52.1 IPS |
|
|
Text Classification (SP)
|
100% |
459
612.8 IPS |
|
|
Text Classification (HP)
|
100% |
461
615.8 IPS |
|
|
Text Classification (Q)
|
91% |
753
1.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
712
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
704
12.1 IPS |
|
|
Machine Translation (Q)
|
57% |
607
14.8 IPS |
