Samsung Galaxy S24
Geekbench AI Score
2174
Single Precision Score
2149
Half Precision Score
2910
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | TheSub |
| Upload Date | January 28 2026 02:19 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2249
418.2 IPS |
|
|
Image Classification (HP)
|
100% |
2264
421.1 IPS |
|
|
Image Classification (Q)
|
100% |
3250
604.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2317
37.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2487
40.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
3609
58.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3880
4.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3172
3.70 IPS |
|
|
Pose Estimation (Q)
|
84% |
6075
7.20 IPS |
|
|
Object Detection (SP)
|
98% |
1478
117.6 IPS |
|
|
Object Detection (HP)
|
98% |
1479
117.6 IPS |
|
|
Object Detection (Q)
|
83% |
1717
138.7 IPS |
|
|
Face Detection (SP)
|
100% |
3085
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
3099
36.8 IPS |
|
|
Face Detection (Q)
|
95% |
4170
49.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
2973
23.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2929
22.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
4303
39.4 IPS |
|
|
Style Transfer (SP)
|
89% |
7219
9.37 IPS |
|
|
Style Transfer (HP)
|
89% |
7230
9.39 IPS |
|
|
Style Transfer (Q)
|
98% |
12713
16.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1542
56.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1537
56.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3071
113.8 IPS |
|
|
Text Classification (SP)
|
100% |
532
710.2 IPS |
|
|
Text Classification (HP)
|
99% |
562
749.9 IPS |
|
|
Text Classification (Q)
|
88% |
835
1.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
1455
25.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1405
24.2 IPS |
|
|
Machine Translation (Q)
|
50% |
610
21.6 IPS |
