Samsung Galaxy S24+
Geekbench AI Score
1565
Single Precision Score
1858
Half Precision Score
1787
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | aleks7900 |
| Upload Date | December 16 2024 01:31 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926B |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
666
123.8 IPS |
|
|
Image Classification (HP)
|
100% |
814
151.4 IPS |
|
|
Image Classification (Q)
|
99% |
729
136.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1433
23.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2023
32.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1578
25.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3471
4.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
4370
5.10 IPS |
|
|
Pose Estimation (Q)
|
96% |
3927
4.60 IPS |
|
|
Object Detection (SP)
|
100% |
799
63.4 IPS |
|
|
Object Detection (HP)
|
100% |
992
78.7 IPS |
|
|
Object Detection (Q)
|
86% |
1008
81.0 IPS |
|
|
Face Detection (SP)
|
100% |
2617
31.1 IPS |
|
|
Face Detection (HP)
|
100% |
2878
34.2 IPS |
|
|
Face Detection (Q)
|
97% |
2583
30.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
3438
26.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3607
27.9 IPS |
|
|
Depth Estimation (Q)
|
63% |
2848
26.6 IPS |
|
|
Style Transfer (SP)
|
100% |
9090
11.7 IPS |
|
|
Style Transfer (HP)
|
100% |
13028
16.7 IPS |
|
|
Style Transfer (Q)
|
98% |
12695
16.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1606
59.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2008
74.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2088
77.4 IPS |
|
|
Text Classification (SP)
|
100% |
411
548.9 IPS |
|
|
Text Classification (HP)
|
100% |
416
555.5 IPS |
|
|
Text Classification (Q)
|
91% |
703
944.7 IPS |
|
|
Machine Translation (SP)
|
100% |
617
10.6 IPS |
|
|
Machine Translation (HP)
|
100% |
610
10.5 IPS |
|
|
Machine Translation (Q)
|
57% |
532
13.0 IPS |
