Samsung Galaxy S24
Geekbench AI Score
2044
Single Precision Score
2055
Half Precision Score
2887
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | paz_levi |
| Upload Date | August 27 2025 05:28 PM |
| Views | 6 |
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% |
1684
313.2 IPS |
|
|
Image Classification (HP)
|
100% |
1803
335.3 IPS |
|
|
Image Classification (Q)
|
100% |
2999
557.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2288
37.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2320
37.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
3555
57.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3734
4.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
3102
3.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
6080
7.21 IPS |
|
|
Object Detection (SP)
|
98% |
1457
115.9 IPS |
|
|
Object Detection (HP)
|
98% |
1331
105.9 IPS |
|
|
Object Detection (Q)
|
83% |
1810
146.2 IPS |
|
|
Face Detection (SP)
|
100% |
3008
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
3029
36.0 IPS |
|
|
Face Detection (Q)
|
95% |
4425
52.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
3024
23.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3086
23.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
4532
41.5 IPS |
|
|
Style Transfer (SP)
|
89% |
7468
9.69 IPS |
|
|
Style Transfer (HP)
|
89% |
7434
9.65 IPS |
|
|
Style Transfer (Q)
|
98% |
12707
16.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1508
55.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1528
56.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2971
110.1 IPS |
|
|
Text Classification (SP)
|
100% |
522
696.7 IPS |
|
|
Text Classification (HP)
|
99% |
550
734.1 IPS |
|
|
Text Classification (Q)
|
88% |
767
1.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
1137
19.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1336
23.0 IPS |
|
|
Machine Translation (Q)
|
50% |
592
21.0 IPS |
