Samsung Galaxy S24
Geekbench AI Score
2010
Single Precision Score
1976
Half Precision Score
2848
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | TheSub |
| Upload Date | December 20 2025 02:19 PM |
| Views | 20 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 |
| Model ID | samsung SM-S921B |
| 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 | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1968
365.9 IPS |
|
|
Image Classification (HP)
|
100% |
1903
353.8 IPS |
|
|
Image Classification (Q)
|
100% |
2981
554.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2363
38.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2209
35.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
3494
56.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3764
4.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
3553
4.15 IPS |
|
|
Pose Estimation (Q)
|
84% |
6264
7.43 IPS |
|
|
Object Detection (SP)
|
98% |
1234
98.2 IPS |
|
|
Object Detection (HP)
|
98% |
1265
100.7 IPS |
|
|
Object Detection (Q)
|
83% |
1896
153.2 IPS |
|
|
Face Detection (SP)
|
100% |
3067
36.4 IPS |
|
|
Face Detection (HP)
|
100% |
3126
37.1 IPS |
|
|
Face Detection (Q)
|
95% |
4372
52.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
2410
18.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2493
19.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
3916
35.9 IPS |
|
|
Style Transfer (SP)
|
89% |
6407
8.32 IPS |
|
|
Style Transfer (HP)
|
89% |
6710
8.71 IPS |
|
|
Style Transfer (Q)
|
98% |
12346
15.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1368
50.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1462
54.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3074
113.9 IPS |
|
|
Text Classification (SP)
|
100% |
564
752.3 IPS |
|
|
Text Classification (HP)
|
99% |
526
701.5 IPS |
|
|
Text Classification (Q)
|
88% |
818
1.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
1368
23.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1196
20.6 IPS |
|
|
Machine Translation (Q)
|
50% |
535
19.0 IPS |
