Samsung Galaxy S24+
Geekbench AI Score
2320
Single Precision Score
2227
Half Precision Score
3284
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | wishbone521 |
| Upload Date | August 23 2025 07:34 PM |
| Views | 7 |
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-S926B |
| 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 | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1934
359.7 IPS |
|
|
Image Classification (HP)
|
100% |
2119
394.0 IPS |
|
|
Image Classification (Q)
|
100% |
2915
542.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2373
38.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2327
37.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3624
58.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3993
4.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
3600
4.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
7631
9.05 IPS |
|
|
Object Detection (SP)
|
98% |
1770
140.9 IPS |
|
|
Object Detection (HP)
|
98% |
1589
126.4 IPS |
|
|
Object Detection (Q)
|
83% |
2299
185.7 IPS |
|
|
Face Detection (SP)
|
100% |
3512
41.7 IPS |
|
|
Face Detection (HP)
|
100% |
3424
40.7 IPS |
|
|
Face Detection (Q)
|
95% |
5368
64.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3583
27.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
3281
25.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
4795
43.9 IPS |
|
|
Style Transfer (SP)
|
89% |
7861
10.2 IPS |
|
|
Style Transfer (HP)
|
89% |
7802
10.1 IPS |
|
|
Style Transfer (Q)
|
98% |
14320
18.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1624
60.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1613
59.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3400
126.0 IPS |
|
|
Text Classification (SP)
|
100% |
580
774.0 IPS |
|
|
Text Classification (HP)
|
99% |
586
781.9 IPS |
|
|
Text Classification (Q)
|
88% |
938
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
1496
25.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1287
22.2 IPS |
|
|
Machine Translation (Q)
|
50% |
670
23.8 IPS |
