Samsung Galaxy S24+
Geekbench AI Score
2414
Single Precision Score
2458
Half Precision Score
3611
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | ebarak |
| Upload Date | December 20 2024 12:32 AM |
| Views | 9 |
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-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 | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2012
374.2 IPS |
|
|
Image Classification (HP)
|
100% |
2249
418.3 IPS |
|
|
Image Classification (Q)
|
100% |
3244
603.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2363
38.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2319
37.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
3952
64.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3851
4.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
3737
4.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
7641
9.06 IPS |
|
|
Object Detection (SP)
|
98% |
1572
125.1 IPS |
|
|
Object Detection (HP)
|
98% |
1780
141.6 IPS |
|
|
Object Detection (Q)
|
83% |
2476
200.0 IPS |
|
|
Face Detection (SP)
|
100% |
3521
41.8 IPS |
|
|
Face Detection (HP)
|
100% |
3623
43.1 IPS |
|
|
Face Detection (Q)
|
95% |
5269
62.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
3648
28.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3868
29.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
5867
53.7 IPS |
|
|
Style Transfer (SP)
|
89% |
9023
11.7 IPS |
|
|
Style Transfer (HP)
|
89% |
9010
11.7 IPS |
|
|
Style Transfer (Q)
|
98% |
15790
20.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1845
68.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1788
66.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3798
140.7 IPS |
|
|
Text Classification (SP)
|
100% |
660
881.5 IPS |
|
|
Text Classification (HP)
|
99% |
631
842.3 IPS |
|
|
Text Classification (Q)
|
88% |
1074
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1659
28.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1635
28.2 IPS |
|
|
Machine Translation (Q)
|
50% |
781
27.7 IPS |
