Samsung Galaxy S24
Geekbench AI Score
1306
Single Precision Score
2533
Half Precision Score
1861
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Acux6 |
| Upload Date | November 29 2025 12:51 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
799
148.5 IPS |
|
|
Image Classification (HP)
|
100% |
1422
264.5 IPS |
|
|
Image Classification (Q)
|
100% |
1359
252.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1377
22.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2437
39.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2286
37.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6422
7.49 IPS |
|
|
Pose Estimation (HP)
|
99% |
12645
14.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
12449
14.6 IPS |
|
|
Object Detection (SP)
|
100% |
581
46.1 IPS |
|
|
Object Detection (HP)
|
99% |
1021
81.0 IPS |
|
|
Object Detection (Q)
|
84% |
950
76.7 IPS |
|
|
Face Detection (SP)
|
100% |
2611
31.0 IPS |
|
|
Face Detection (HP)
|
100% |
4691
55.7 IPS |
|
|
Face Detection (Q)
|
97% |
3953
47.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3680
28.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
7064
54.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
5183
50.0 IPS |
|
|
Style Transfer (SP)
|
100% |
13280
17.1 IPS |
|
|
Style Transfer (HP)
|
100% |
24216
31.1 IPS |
|
|
Style Transfer (Q)
|
98% |
24238
31.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1783
65.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3354
123.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3656
135.5 IPS |
|
|
Text Classification (SP)
|
29% |
22
388.1 IPS |
|
|
Text Classification (HP)
|
35% |
93
843.9 IPS |
|
|
Text Classification (Q)
|
31% |
38
562.1 IPS |
|
|
Machine Translation (SP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
973
16.8 IPS |
|
|
Machine Translation (Q)
|
42% |
197
12.7 IPS |
