Samsung Galaxy S24+
Geekbench AI Score
2198
Single Precision Score
2249
Half Precision Score
3177
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | aleks7900 |
| Upload Date | December 16 2024 01:27 PM |
| 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-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% |
1738
323.2 IPS |
|
|
Image Classification (HP)
|
100% |
1978
367.8 IPS |
|
|
Image Classification (Q)
|
100% |
2995
556.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2263
36.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2324
37.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3488
56.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3667
4.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
3580
4.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
7611
9.03 IPS |
|
|
Object Detection (SP)
|
98% |
1614
128.4 IPS |
|
|
Object Detection (HP)
|
98% |
1612
128.3 IPS |
|
|
Object Detection (Q)
|
83% |
1976
159.6 IPS |
|
|
Face Detection (SP)
|
100% |
3149
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
3274
38.9 IPS |
|
|
Face Detection (Q)
|
95% |
4621
55.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3158
24.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3242
25.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
4750
43.5 IPS |
|
|
Style Transfer (SP)
|
89% |
7813
10.1 IPS |
|
|
Style Transfer (HP)
|
89% |
7778
10.1 IPS |
|
|
Style Transfer (Q)
|
98% |
14367
18.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1680
62.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1711
63.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3432
127.2 IPS |
|
|
Text Classification (SP)
|
100% |
619
826.3 IPS |
|
|
Text Classification (HP)
|
99% |
610
814.3 IPS |
|
|
Text Classification (Q)
|
88% |
943
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
1403
24.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1451
25.0 IPS |
|
|
Machine Translation (Q)
|
50% |
654
23.2 IPS |
