Samsung Galaxy S24+
Geekbench AI Score
1258
Single Precision Score
2319
Half Precision Score
1751
Quantized Score
Geekbench AI 1.6.0 Corporate for Android AArch64
Result Information
| Upload Date | December 02 2025 08:11 PM |
| Views | 5 |
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-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 | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
745
138.5 IPS |
|
|
Image Classification (HP)
|
100% |
1236
229.8 IPS |
|
|
Image Classification (Q)
|
100% |
1125
209.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1339
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2426
39.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2273
37.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
5906
6.89 IPS |
|
|
Pose Estimation (HP)
|
99% |
12170
14.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
12069
14.1 IPS |
|
|
Object Detection (SP)
|
100% |
567
44.9 IPS |
|
|
Object Detection (HP)
|
99% |
960
76.2 IPS |
|
|
Object Detection (Q)
|
84% |
899
72.6 IPS |
|
|
Face Detection (SP)
|
100% |
2456
29.2 IPS |
|
|
Face Detection (HP)
|
100% |
4137
49.2 IPS |
|
|
Face Detection (Q)
|
97% |
3917
46.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3439
26.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
6419
49.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
4721
45.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12713
16.3 IPS |
|
|
Style Transfer (HP)
|
100% |
23100
29.7 IPS |
|
|
Style Transfer (Q)
|
98% |
22870
29.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1673
61.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3484
128.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3370
124.9 IPS |
|
|
Text Classification (SP)
|
29% |
24
411.9 IPS |
|
|
Text Classification (HP)
|
35% |
62
564.4 IPS |
|
|
Text Classification (Q)
|
30% |
35
555.6 IPS |
|
|
Machine Translation (SP)
|
100% |
692
11.9 IPS |
|
|
Machine Translation (HP)
|
100% |
972
16.7 IPS |
|
|
Machine Translation (Q)
|
42% |
196
12.7 IPS |
