Samsung Galaxy S24
Geekbench AI Score
1678
Single Precision Score
1473
Half Precision Score
1452
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | coladelicious |
| Upload Date | February 23 2025 04:53 AM |
| Views | 4 |
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-S921N |
| 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 | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1185
220.3 IPS |
|
|
Image Classification (HP)
|
100% |
930
172.9 IPS |
|
|
Image Classification (Q)
|
99% |
799
149.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1569
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1714
27.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1531
24.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3516
4.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
2488
2.90 IPS |
|
|
Pose Estimation (Q)
|
96% |
2432
2.85 IPS |
|
|
Object Detection (SP)
|
100% |
818
64.9 IPS |
|
|
Object Detection (HP)
|
100% |
622
49.3 IPS |
|
|
Object Detection (Q)
|
86% |
614
49.4 IPS |
|
|
Face Detection (SP)
|
100% |
2163
25.7 IPS |
|
|
Face Detection (HP)
|
100% |
2818
33.5 IPS |
|
|
Face Detection (Q)
|
97% |
2300
27.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
3198
24.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2423
18.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
2058
19.2 IPS |
|
|
Style Transfer (SP)
|
100% |
9201
11.8 IPS |
|
|
Style Transfer (HP)
|
100% |
7477
9.61 IPS |
|
|
Style Transfer (Q)
|
98% |
7455
9.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1587
58.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1195
44.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1445
53.5 IPS |
|
|
Text Classification (SP)
|
100% |
468
625.2 IPS |
|
|
Text Classification (HP)
|
100% |
465
620.4 IPS |
|
|
Text Classification (Q)
|
91% |
755
1.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
701
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
688
11.9 IPS |
|
|
Machine Translation (Q)
|
57% |
593
14.5 IPS |
