Samsung Galaxy S24 Ultra
Geekbench AI Score
372
Single Precision Score
364
Half Precision Score
806
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Spiike |
| Upload Date | July 16 2025 02:08 AM |
| Views | 3 |
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% |
299
55.7 IPS |
|
|
Image Classification (HP)
|
100% |
299
55.6 IPS |
|
|
Image Classification (Q)
|
99% |
764
142.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
375
6.08 IPS |
|
|
Image Segmentation (HP)
|
100% |
324
5.26 IPS |
|
|
Image Segmentation (Q)
|
98% |
652
10.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
396
0.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
366
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1359
1.59 IPS |
|
|
Object Detection (SP)
|
100% |
200
15.9 IPS |
|
|
Object Detection (HP)
|
100% |
199
15.8 IPS |
|
|
Object Detection (Q)
|
87% |
559
44.8 IPS |
|
|
Face Detection (SP)
|
100% |
503
5.97 IPS |
|
|
Face Detection (HP)
|
100% |
507
6.03 IPS |
|
|
Face Detection (Q)
|
97% |
1161
13.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
456
3.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
458
3.53 IPS |
|
|
Depth Estimation (Q)
|
64% |
1022
9.27 IPS |
|
|
Style Transfer (SP)
|
100% |
742
0.95 IPS |
|
|
Style Transfer (HP)
|
100% |
733
0.94 IPS |
|
|
Style Transfer (Q)
|
98% |
1758
2.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
243
8.96 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
243
8.97 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
793
29.4 IPS |
|
|
Text Classification (SP)
|
100% |
289
386.0 IPS |
|
|
Text Classification (HP)
|
100% |
291
389.0 IPS |
|
|
Text Classification (Q)
|
91% |
477
640.7 IPS |
|
|
Machine Translation (SP)
|
100% |
483
8.31 IPS |
|
|
Machine Translation (HP)
|
100% |
486
8.37 IPS |
|
|
Machine Translation (Q)
|
57% |
390
9.53 IPS |
