Samsung Galaxy S24+
Geekbench AI Score
1607
Single Precision Score
2456
Half Precision Score
2120
Quantized Score
Geekbench AI 1.5.0 Corporate for Android AArch64
Result Information
| Upload Date | September 02 2025 08:02 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926N |
| 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 | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
866
161.1 IPS |
|
|
Image Classification (HP)
|
100% |
1297
241.3 IPS |
|
|
Image Classification (Q)
|
100% |
1188
220.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1973
32.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2769
44.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
2458
40.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8561
9.99 IPS |
|
|
Pose Estimation (HP)
|
99% |
14901
17.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
10369
12.2 IPS |
|
|
Object Detection (SP)
|
100% |
669
53.1 IPS |
|
|
Object Detection (HP)
|
99% |
1133
89.9 IPS |
|
|
Object Detection (Q)
|
85% |
1043
84.0 IPS |
|
|
Face Detection (SP)
|
100% |
2720
32.3 IPS |
|
|
Face Detection (HP)
|
100% |
5641
67.0 IPS |
|
|
Face Detection (Q)
|
97% |
3862
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3999
30.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
6813
52.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
5654
55.9 IPS |
|
|
Style Transfer (SP)
|
100% |
15485
19.9 IPS |
|
|
Style Transfer (HP)
|
100% |
22969
29.5 IPS |
|
|
Style Transfer (Q)
|
98% |
27567
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2052
75.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3904
144.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4526
167.7 IPS |
|
|
Text Classification (SP)
|
29% |
34
581.9 IPS |
|
|
Text Classification (HP)
|
29% |
35
611.3 IPS |
|
|
Text Classification (Q)
|
33% |
52
619.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1001
17.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1096
18.9 IPS |
|
|
Machine Translation (Q)
|
48% |
410
15.7 IPS |
