Samsung Galaxy S24+
Geekbench AI Score
2372
Single Precision Score
2437
Half Precision Score
3492
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | SExynos024 |
| Upload Date | February 02 2025 01:23 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1680
312.5 IPS |
|
|
Image Classification (HP)
|
100% |
2101
390.7 IPS |
|
|
Image Classification (Q)
|
100% |
2860
531.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2350
38.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2327
37.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3537
57.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3961
4.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
3917
4.57 IPS |
|
|
Pose Estimation (Q)
|
84% |
8698
10.3 IPS |
|
|
Object Detection (SP)
|
98% |
1771
140.9 IPS |
|
|
Object Detection (HP)
|
98% |
1771
140.9 IPS |
|
|
Object Detection (Q)
|
83% |
2231
180.2 IPS |
|
|
Face Detection (SP)
|
100% |
3423
40.7 IPS |
|
|
Face Detection (HP)
|
100% |
3433
40.8 IPS |
|
|
Face Detection (Q)
|
95% |
5172
61.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
3396
26.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3602
27.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5809
53.2 IPS |
|
|
Style Transfer (SP)
|
89% |
9251
12.0 IPS |
|
|
Style Transfer (HP)
|
89% |
8774
11.4 IPS |
|
|
Style Transfer (Q)
|
98% |
15687
20.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1825
67.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1797
66.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3846
142.5 IPS |
|
|
Text Classification (SP)
|
100% |
663
885.6 IPS |
|
|
Text Classification (HP)
|
99% |
697
930.9 IPS |
|
|
Text Classification (Q)
|
88% |
969
1.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
1565
27.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1609
27.7 IPS |
|
|
Machine Translation (Q)
|
50% |
783
27.8 IPS |
