Samsung Galaxy S24 Ultra
Geekbench AI Score
419
Single Precision Score
406
Half Precision Score
886
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 16 2025 08:24 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928U1 |
| 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% |
313
58.2 IPS |
|
|
Image Classification (HP)
|
100% |
310
57.7 IPS |
|
|
Image Classification (Q)
|
99% |
809
150.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
394
6.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
396
6.42 IPS |
|
|
Image Segmentation (Q)
|
98% |
794
12.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
539
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
417
0.49 IPS |
|
|
Pose Estimation (Q)
|
98% |
1565
1.83 IPS |
|
|
Object Detection (SP)
|
100% |
225
17.9 IPS |
|
|
Object Detection (HP)
|
100% |
231
18.3 IPS |
|
|
Object Detection (Q)
|
87% |
636
51.0 IPS |
|
|
Face Detection (SP)
|
100% |
593
7.05 IPS |
|
|
Face Detection (HP)
|
100% |
601
7.14 IPS |
|
|
Face Detection (Q)
|
97% |
1310
15.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
502
3.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
468
3.60 IPS |
|
|
Depth Estimation (Q)
|
64% |
1018
9.24 IPS |
|
|
Style Transfer (SP)
|
100% |
780
1.00 IPS |
|
|
Style Transfer (HP)
|
100% |
762
0.98 IPS |
|
|
Style Transfer (Q)
|
98% |
1918
2.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
273
10.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
272
10.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
887
32.9 IPS |
|
|
Text Classification (SP)
|
100% |
315
420.7 IPS |
|
|
Text Classification (HP)
|
100% |
316
421.5 IPS |
|
|
Text Classification (Q)
|
91% |
529
710.7 IPS |
|
|
Machine Translation (SP)
|
100% |
560
9.65 IPS |
|
|
Machine Translation (HP)
|
100% |
562
9.68 IPS |
|
|
Machine Translation (Q)
|
57% |
392
9.58 IPS |
