Samsung Galaxy S24 FE
Geekbench AI Score
1472
Single Precision Score
2666
Half Precision Score
1894
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | joao2 |
| Upload Date | February 09 2026 09:57 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2400e |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 FE |
| Model ID | samsung SM-S721B |
| 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 @ 3.11 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1251
232.6 IPS |
|
|
Image Classification (HP)
|
100% |
1900
353.4 IPS |
|
|
Image Classification (Q)
|
100% |
1275
237.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1916
31.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
3309
53.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2552
41.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5809
6.78 IPS |
|
|
Pose Estimation (HP)
|
99% |
12533
14.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
12408
14.5 IPS |
|
|
Object Detection (SP)
|
100% |
594
47.1 IPS |
|
|
Object Detection (HP)
|
99% |
1029
81.6 IPS |
|
|
Object Detection (Q)
|
84% |
964
77.8 IPS |
|
|
Face Detection (SP)
|
100% |
2590
30.8 IPS |
|
|
Face Detection (HP)
|
100% |
4476
53.2 IPS |
|
|
Face Detection (Q)
|
97% |
4441
53.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3684
28.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
6299
48.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
4898
47.2 IPS |
|
|
Style Transfer (SP)
|
100% |
13378
17.2 IPS |
|
|
Style Transfer (HP)
|
100% |
22950
29.5 IPS |
|
|
Style Transfer (Q)
|
98% |
18423
23.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1676
61.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3377
124.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3535
131.0 IPS |
|
|
Text Classification (SP)
|
29% |
40
691.7 IPS |
|
|
Text Classification (HP)
|
35% |
96
876.4 IPS |
|
|
Text Classification (Q)
|
30% |
51
815.9 IPS |
|
|
Machine Translation (SP)
|
100% |
679
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1068
18.4 IPS |
|
|
Machine Translation (Q)
|
42% |
212
13.8 IPS |
