Samsung Galaxy S24 FE
Geekbench AI Score
267
Single Precision Score
273
Half Precision Score
785
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | joao2 |
| Upload Date | February 09 2026 10:13 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
275
51.1 IPS |
|
|
Image Classification (HP)
|
100% |
249
46.4 IPS |
|
|
Image Classification (Q)
|
99% |
678
126.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
914
14.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1431
23.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
688
11.2 IPS |
|
|
Pose Estimation (SP)
|
0
|
||
|
Pose Estimation (HP)
|
0
|
||
|
Pose Estimation (Q)
|
98% |
1734
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
239
19.0 IPS |
|
|
Object Detection (HP)
|
100% |
242
19.2 IPS |
|
|
Object Detection (Q)
|
87% |
734
58.8 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
561
6.67 IPS |
|
|
Face Detection (Q)
|
97% |
1243
14.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
472
3.63 IPS |
|
|
Depth Estimation (HP)
|
99% |
414
3.19 IPS |
|
|
Depth Estimation (Q)
|
64% |
875
7.94 IPS |
|
|
Style Transfer (SP)
|
100% |
650
0.84 IPS |
|
|
Style Transfer (HP)
|
100% |
648
0.83 IPS |
|
|
Style Transfer (Q)
|
98% |
1503
1.94 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1400
51.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1636
60.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
688
25.5 IPS |
|
|
Text Classification (SP)
|
100% |
259
346.1 IPS |
|
|
Text Classification (HP)
|
100% |
259
345.8 IPS |
|
|
Text Classification (Q)
|
91% |
407
546.4 IPS |
|
|
Machine Translation (SP)
|
100% |
459
7.90 IPS |
|
|
Machine Translation (HP)
|
100% |
432
7.45 IPS |
|
|
Machine Translation (Q)
|
57% |
328
8.02 IPS |
