Samsung Galaxy S24
Geekbench AI Score
2464
Single Precision Score
2410
Half Precision Score
3758
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | thanosk |
| Upload Date | September 22 2025 07:41 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24 |
| Model ID | samsung SM-S921B |
| 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% |
1796
334.0 IPS |
|
|
Image Classification (HP)
|
100% |
1758
326.9 IPS |
|
|
Image Classification (Q)
|
100% |
3215
598.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2479
40.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2321
37.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
3866
62.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3913
4.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
3808
4.44 IPS |
|
|
Pose Estimation (Q)
|
84% |
8719
10.3 IPS |
|
|
Object Detection (SP)
|
98% |
1916
152.5 IPS |
|
|
Object Detection (HP)
|
98% |
1676
133.4 IPS |
|
|
Object Detection (Q)
|
83% |
2657
214.6 IPS |
|
|
Face Detection (SP)
|
100% |
3709
44.1 IPS |
|
|
Face Detection (HP)
|
100% |
3832
45.5 IPS |
|
|
Face Detection (Q)
|
95% |
6397
76.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
4150
32.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4076
31.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
6627
60.7 IPS |
|
|
Style Transfer (SP)
|
89% |
8302
10.8 IPS |
|
|
Style Transfer (HP)
|
89% |
8464
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
14977
19.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1736
64.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1791
66.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3795
140.6 IPS |
|
|
Text Classification (SP)
|
100% |
683
911.6 IPS |
|
|
Text Classification (HP)
|
99% |
763
1.02 KIPS |
|
|
Text Classification (Q)
|
88% |
1187
1.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
1636
28.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1408
24.3 IPS |
|
|
Machine Translation (Q)
|
50% |
683
24.3 IPS |
