Samsung Galaxy S24
Geekbench AI Score
1239
Single Precision Score
2237
Half Precision Score
1660
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | paz_levi |
| Upload Date | August 27 2025 05:31 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
695
129.3 IPS |
|
|
Image Classification (HP)
|
100% |
1118
207.8 IPS |
|
|
Image Classification (Q)
|
100% |
1020
189.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1476
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2289
37.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2060
33.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6179
7.21 IPS |
|
|
Pose Estimation (HP)
|
99% |
12963
15.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
10388
12.2 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
99% |
768
60.9 IPS |
|
|
Object Detection (Q)
|
84% |
877
70.7 IPS |
|
|
Face Detection (SP)
|
100% |
2540
30.2 IPS |
|
|
Face Detection (HP)
|
100% |
4171
49.6 IPS |
|
|
Face Detection (Q)
|
97% |
3678
43.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
3513
27.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
6161
47.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
4833
46.6 IPS |
|
|
Style Transfer (SP)
|
100% |
12022
15.5 IPS |
|
|
Style Transfer (HP)
|
100% |
21941
28.2 IPS |
|
|
Style Transfer (Q)
|
98% |
22335
28.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1794
66.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3506
129.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3371
124.9 IPS |
|
|
Text Classification (SP)
|
29% |
22
378.7 IPS |
|
|
Text Classification (HP)
|
35% |
64
578.2 IPS |
|
|
Text Classification (Q)
|
29% |
32
560.9 IPS |
|
|
Machine Translation (SP)
|
100% |
699
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
974
16.8 IPS |
|
|
Machine Translation (Q)
|
42% |
194
12.6 IPS |
