Samsung Galaxy S24 Ultra
Geekbench AI Score
2380
Single Precision Score
2490
Half Precision Score
3750
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 22 2025 10:02 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928B |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1921
357.3 IPS |
|
|
Image Classification (HP)
|
100% |
2350
437.1 IPS |
|
|
Image Classification (Q)
|
100% |
3391
630.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2629
42.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2589
42.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4171
67.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4346
5.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
4217
4.92 IPS |
|
|
Pose Estimation (Q)
|
84% |
8345
9.90 IPS |
|
|
Object Detection (SP)
|
98% |
1793
142.7 IPS |
|
|
Object Detection (HP)
|
98% |
1782
141.8 IPS |
|
|
Object Detection (Q)
|
83% |
2566
207.3 IPS |
|
|
Face Detection (SP)
|
100% |
3307
39.3 IPS |
|
|
Face Detection (HP)
|
100% |
3289
39.1 IPS |
|
|
Face Detection (Q)
|
95% |
5658
67.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2754
21.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
3450
26.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5712
52.3 IPS |
|
|
Style Transfer (SP)
|
89% |
8737
11.3 IPS |
|
|
Style Transfer (HP)
|
89% |
8691
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16672
21.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1694
62.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1730
63.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4240
157.1 IPS |
|
|
Text Classification (SP)
|
100% |
725
968.0 IPS |
|
|
Text Classification (HP)
|
99% |
770
1.03 KIPS |
|
|
Text Classification (Q)
|
88% |
1085
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1521
26.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1529
26.3 IPS |
|
|
Machine Translation (Q)
|
50% |
734
26.0 IPS |
