Samsung Galaxy S24+
Geekbench AI Score
2799
Single Precision Score
2764
Half Precision Score
4423
Quantized Score
Geekbench AI 1.0.0 Corporate for Android AArch64
Result Information
| Upload Date | August 11 2024 08:41 AM |
| Views | 7 |
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% |
2292
426.2 IPS |
|
|
Image Classification (HP)
|
100% |
2275
423.1 IPS |
|
|
Image Classification (Q)
|
100% |
3502
651.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2583
41.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2578
41.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
4048
65.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4269
4.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
4125
4.81 IPS |
|
|
Pose Estimation (Q)
|
84% |
9506
11.3 IPS |
|
|
Object Detection (SP)
|
98% |
2133
169.7 IPS |
|
|
Object Detection (HP)
|
98% |
2134
169.8 IPS |
|
|
Object Detection (Q)
|
87% |
3419
274.6 IPS |
|
|
Face Detection (SP)
|
100% |
4129
49.1 IPS |
|
|
Face Detection (HP)
|
100% |
4175
49.6 IPS |
|
|
Face Detection (Q)
|
95% |
7529
89.9 IPS |
|
|
Depth Estimation (SP)
|
98% |
3763
29.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3707
28.6 IPS |
|
|
Depth Estimation (Q)
|
75% |
7746
62.8 IPS |
|
|
Style Transfer (SP)
|
89% |
10373
13.5 IPS |
|
|
Style Transfer (HP)
|
89% |
10041
13.0 IPS |
|
|
Style Transfer (Q)
|
98% |
19848
25.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2164
79.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2166
80.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4830
179.0 IPS |
|
|
Text Classification (SP)
|
100% |
881
1.18 KIPS |
|
|
Text Classification (HP)
|
99% |
880
1.18 KIPS |
|
|
Text Classification (Q)
|
88% |
1185
1.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
1782
30.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1704
29.4 IPS |
|
|
Machine Translation (Q)
|
50% |
939
33.3 IPS |
