Samsung Galaxy S24+
Geekbench AI Score
2665
Single Precision Score
2598
Half Precision Score
4000
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | ShowXTech |
| Upload Date | June 18 2025 12:56 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2312
430.0 IPS |
|
|
Image Classification (HP)
|
100% |
2195
408.2 IPS |
|
|
Image Classification (Q)
|
100% |
3285
610.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2546
41.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2580
41.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
3952
64.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4098
4.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
4069
4.75 IPS |
|
|
Pose Estimation (Q)
|
84% |
9197
10.9 IPS |
|
|
Object Detection (SP)
|
98% |
2032
161.7 IPS |
|
|
Object Detection (HP)
|
98% |
1956
155.6 IPS |
|
|
Object Detection (Q)
|
83% |
3077
248.5 IPS |
|
|
Face Detection (SP)
|
100% |
3907
46.4 IPS |
|
|
Face Detection (HP)
|
100% |
4054
48.2 IPS |
|
|
Face Detection (Q)
|
95% |
6799
81.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3701
28.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
3567
27.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
6828
62.5 IPS |
|
|
Style Transfer (SP)
|
89% |
10009
13.0 IPS |
|
|
Style Transfer (HP)
|
89% |
10009
13.0 IPS |
|
|
Style Transfer (Q)
|
98% |
20037
25.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2083
76.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2026
74.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4422
163.9 IPS |
|
|
Text Classification (SP)
|
100% |
759
1.01 KIPS |
|
|
Text Classification (HP)
|
99% |
732
977.3 IPS |
|
|
Text Classification (Q)
|
88% |
1003
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
1614
27.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1448
24.9 IPS |
|
|
Machine Translation (Q)
|
50% |
693
24.6 IPS |
