Samsung Galaxy S24+
Geekbench AI Score
3555
Single Precision Score
25166
Half Precision Score
46432
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 13 2024 10:12 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926B |
| 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 | 6.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1603
298.1 IPS |
|
|
Image Classification (HP)
|
100% |
17049
3.17 KIPS |
|
|
Image Classification (Q)
|
100% |
32842
6.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3020
49.0 IPS |
|
|
Image Segmentation (HP)
|
97% |
12641
205.6 IPS |
|
|
Image Segmentation (Q)
|
96% |
28680
466.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
14666
17.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
88272
103.0 IPS |
|
|
Pose Estimation (Q)
|
97% |
303183
355.0 IPS |
|
|
Object Detection (SP)
|
100% |
1592
126.3 IPS |
|
|
Object Detection (HP)
|
100% |
14025
1.11 KIPS |
|
|
Object Detection (Q)
|
90% |
21192
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
5060
60.1 IPS |
|
|
Face Detection (HP)
|
100% |
39768
472.5 IPS |
|
|
Face Detection (Q)
|
97% |
101612
1.21 KIPS |
|
|
Depth Estimation (SP)
|
100% |
5636
43.4 IPS |
|
|
Depth Estimation (HP)
|
79% |
56623
449.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
106571
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
29458
37.9 IPS |
|
|
Style Transfer (HP)
|
99% |
174591
224.4 IPS |
|
|
Style Transfer (Q)
|
98% |
264970
341.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4173
154.1 IPS |
|
|
Image Super-Resolution (HP)
|
84% |
22916
861.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
58455
2.17 KIPS |
|
|
Text Classification (SP)
|
100% |
646
861.6 IPS |
|
|
Text Classification (HP)
|
100% |
6868
9.17 KIPS |
|
|
Text Classification (Q)
|
93% |
8136
10.9 KIPS |
|
|
Machine Translation (SP)
|
100% |
1263
21.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6174
106.3 IPS |
|
|
Machine Translation (Q)
|
56% |
5640
144.7 IPS |
