Samsung Galaxy S24 FE
Geekbench AI Score
1315
Single Precision Score
2475
Half Precision Score
1800
Quantized Score
Geekbench AI 1.6.0 Corporate for Android AArch64
Result Information
| Upload Date | December 02 2025 08:11 PM |
| Views | 3 |
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-S721W |
| 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% |
775
144.2 IPS |
|
|
Image Classification (HP)
|
100% |
1619
301.0 IPS |
|
|
Image Classification (Q)
|
100% |
1372
255.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1402
22.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2545
41.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2371
38.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6387
7.45 IPS |
|
|
Pose Estimation (HP)
|
99% |
12650
14.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
12679
14.9 IPS |
|
|
Object Detection (SP)
|
100% |
585
46.4 IPS |
|
|
Object Detection (HP)
|
99% |
1051
83.4 IPS |
|
|
Object Detection (Q)
|
84% |
935
75.4 IPS |
|
|
Face Detection (SP)
|
100% |
2590
30.8 IPS |
|
|
Face Detection (HP)
|
100% |
4842
57.5 IPS |
|
|
Face Detection (Q)
|
97% |
3868
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3736
28.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
6600
51.0 IPS |
|
|
Depth Estimation (Q)
|
62% |
5012
48.3 IPS |
|
|
Style Transfer (SP)
|
100% |
13204
17.0 IPS |
|
|
Style Transfer (HP)
|
100% |
24020
30.9 IPS |
|
|
Style Transfer (Q)
|
98% |
24481
31.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1727
63.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3460
127.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3507
130.0 IPS |
|
|
Text Classification (SP)
|
29% |
25
426.9 IPS |
|
|
Text Classification (HP)
|
35% |
62
567.7 IPS |
|
|
Text Classification (Q)
|
29% |
29
500.6 IPS |
|
|
Machine Translation (SP)
|
100% |
691
11.9 IPS |
|
|
Machine Translation (HP)
|
100% |
959
16.5 IPS |
|
|
Machine Translation (Q)
|
42% |
192
12.4 IPS |
