Samsung Galaxy S24
Geekbench AI Score
1335
Single Precision Score
2467
Half Precision Score
1806
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | TheSub |
| Upload Date | January 28 2026 02:22 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1061
197.3 IPS |
|
|
Image Classification (HP)
|
100% |
2010
373.8 IPS |
|
|
Image Classification (Q)
|
100% |
1309
243.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1359
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2159
35.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2019
32.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5838
6.81 IPS |
|
|
Pose Estimation (HP)
|
99% |
12294
14.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
12878
15.1 IPS |
|
|
Object Detection (SP)
|
100% |
595
47.2 IPS |
|
|
Object Detection (HP)
|
99% |
1013
80.3 IPS |
|
|
Object Detection (Q)
|
84% |
957
77.2 IPS |
|
|
Face Detection (SP)
|
100% |
2672
31.7 IPS |
|
|
Face Detection (HP)
|
100% |
4453
52.9 IPS |
|
|
Face Detection (Q)
|
97% |
4258
50.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
3679
28.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
6860
53.0 IPS |
|
|
Depth Estimation (Q)
|
62% |
4945
47.7 IPS |
|
|
Style Transfer (SP)
|
100% |
13240
17.0 IPS |
|
|
Style Transfer (HP)
|
100% |
23559
30.3 IPS |
|
|
Style Transfer (Q)
|
98% |
23641
30.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1744
64.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3417
126.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3480
129.0 IPS |
|
|
Text Classification (SP)
|
29% |
23
395.8 IPS |
|
|
Text Classification (HP)
|
35% |
64
581.9 IPS |
|
|
Text Classification (Q)
|
30% |
34
550.8 IPS |
|
|
Machine Translation (SP)
|
100% |
688
11.9 IPS |
|
|
Machine Translation (HP)
|
100% |
983
16.9 IPS |
|
|
Machine Translation (Q)
|
42% |
193
12.5 IPS |
