Samsung Galaxy S24+
Geekbench AI Score
1615
Single Precision Score
1930
Half Precision Score
1816
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | wudi890 |
| Upload Date | September 09 2024 08:38 PM |
| Views | 15 |
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-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% |
676
125.7 IPS |
|
|
Image Classification (HP)
|
100% |
811
150.8 IPS |
|
|
Image Classification (Q)
|
99% |
725
135.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1581
25.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2111
34.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1560
25.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
3563
4.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
4564
5.33 IPS |
|
|
Pose Estimation (Q)
|
96% |
4447
5.21 IPS |
|
|
Object Detection (SP)
|
100% |
885
70.2 IPS |
|
|
Object Detection (HP)
|
100% |
949
75.3 IPS |
|
|
Object Detection (Q)
|
86% |
1015
81.6 IPS |
|
|
Face Detection (SP)
|
100% |
2468
29.3 IPS |
|
|
Face Detection (HP)
|
100% |
2893
34.4 IPS |
|
|
Face Detection (Q)
|
97% |
2377
28.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
3022
23.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
3985
30.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
2869
26.8 IPS |
|
|
Style Transfer (SP)
|
100% |
9148
11.8 IPS |
|
|
Style Transfer (HP)
|
100% |
13207
17.0 IPS |
|
|
Style Transfer (Q)
|
98% |
13266
17.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1739
64.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2126
78.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1986
73.6 IPS |
|
|
Text Classification (SP)
|
100% |
450
600.5 IPS |
|
|
Text Classification (HP)
|
100% |
455
607.9 IPS |
|
|
Text Classification (Q)
|
91% |
748
1.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
672
11.6 IPS |
|
|
Machine Translation (HP)
|
100% |
659
11.3 IPS |
|
|
Machine Translation (Q)
|
57% |
569
13.9 IPS |
