Samsung Galaxy S24 Ultra
Geekbench AI Score
470
Single Precision Score
462
Half Precision Score
1035
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Spiike |
| Upload Date | April 13 2025 04:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928W |
| 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% |
310
57.6 IPS |
|
|
Image Classification (HP)
|
100% |
309
57.5 IPS |
|
|
Image Classification (Q)
|
99% |
805
150.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
391
6.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
394
6.39 IPS |
|
|
Image Segmentation (Q)
|
98% |
802
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
531
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
515
0.60 IPS |
|
|
Pose Estimation (Q)
|
98% |
1977
2.31 IPS |
|
|
Object Detection (SP)
|
100% |
287
22.7 IPS |
|
|
Object Detection (HP)
|
100% |
279
22.1 IPS |
|
|
Object Detection (Q)
|
87% |
789
63.3 IPS |
|
|
Face Detection (SP)
|
100% |
683
8.12 IPS |
|
|
Face Detection (HP)
|
100% |
657
7.81 IPS |
|
|
Face Detection (Q)
|
97% |
1534
18.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
591
4.55 IPS |
|
|
Depth Estimation (HP)
|
99% |
563
4.34 IPS |
|
|
Depth Estimation (Q)
|
64% |
1298
11.8 IPS |
|
|
Style Transfer (SP)
|
100% |
912
1.17 IPS |
|
|
Style Transfer (HP)
|
100% |
874
1.12 IPS |
|
|
Style Transfer (Q)
|
98% |
2187
2.82 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
314
11.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
322
11.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1009
37.4 IPS |
|
|
Text Classification (SP)
|
100% |
384
513.0 IPS |
|
|
Text Classification (HP)
|
100% |
385
513.6 IPS |
|
|
Text Classification (Q)
|
91% |
633
851.4 IPS |
|
|
Machine Translation (SP)
|
100% |
652
11.2 IPS |
|
|
Machine Translation (HP)
|
100% |
636
11.0 IPS |
|
|
Machine Translation (Q)
|
57% |
506
12.4 IPS |
