Samsung Galaxy S24
Geekbench AI Score
2313
Single Precision Score
2290
Half Precision Score
3334
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | TheSub |
| Upload Date | December 26 2025 04:20 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1946
361.9 IPS |
|
|
Image Classification (HP)
|
100% |
2174
404.4 IPS |
|
|
Image Classification (Q)
|
100% |
3277
609.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2472
40.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2510
40.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3929
63.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3895
4.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
3886
4.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
8583
10.2 IPS |
|
|
Object Detection (SP)
|
98% |
1705
135.7 IPS |
|
|
Object Detection (HP)
|
98% |
1646
131.0 IPS |
|
|
Object Detection (Q)
|
83% |
2386
192.7 IPS |
|
|
Face Detection (SP)
|
100% |
3486
41.4 IPS |
|
|
Face Detection (HP)
|
100% |
3415
40.6 IPS |
|
|
Face Detection (Q)
|
95% |
5486
65.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
3774
29.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3757
29.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
5183
47.5 IPS |
|
|
Style Transfer (SP)
|
89% |
8333
10.8 IPS |
|
|
Style Transfer (HP)
|
89% |
7238
9.40 IPS |
|
|
Style Transfer (Q)
|
98% |
12675
16.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1510
55.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1505
55.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3224
119.4 IPS |
|
|
Text Classification (SP)
|
100% |
565
754.3 IPS |
|
|
Text Classification (HP)
|
99% |
604
806.0 IPS |
|
|
Text Classification (Q)
|
88% |
914
1.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
1472
25.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1351
23.3 IPS |
|
|
Machine Translation (Q)
|
50% |
607
21.6 IPS |
