Samsung Galaxy S24 Ultra
Geekbench AI Score
426
Single Precision Score
410
Half Precision Score
888
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 16 2025 07:26 PM |
| Views | 7 |
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% |
309
57.5 IPS |
|
|
Image Classification (Q)
|
99% |
811
151.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
393
6.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
398
6.45 IPS |
|
|
Image Segmentation (Q)
|
98% |
792
12.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
541
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
423
0.49 IPS |
|
|
Pose Estimation (Q)
|
98% |
1450
1.70 IPS |
|
|
Object Detection (SP)
|
100% |
231
18.3 IPS |
|
|
Object Detection (HP)
|
100% |
238
18.9 IPS |
|
|
Object Detection (Q)
|
87% |
657
52.7 IPS |
|
|
Face Detection (SP)
|
100% |
611
7.26 IPS |
|
|
Face Detection (HP)
|
100% |
617
7.33 IPS |
|
|
Face Detection (Q)
|
97% |
1311
15.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
512
3.95 IPS |
|
|
Depth Estimation (HP)
|
99% |
481
3.71 IPS |
|
|
Depth Estimation (Q)
|
64% |
1009
9.16 IPS |
|
|
Style Transfer (SP)
|
100% |
793
1.02 IPS |
|
|
Style Transfer (HP)
|
100% |
757
0.97 IPS |
|
|
Style Transfer (Q)
|
98% |
1851
2.39 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
272
10.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
272
10.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
889
32.9 IPS |
|
|
Text Classification (SP)
|
100% |
334
445.8 IPS |
|
|
Text Classification (HP)
|
100% |
335
447.8 IPS |
|
|
Text Classification (Q)
|
91% |
543
729.6 IPS |
|
|
Machine Translation (SP)
|
100% |
577
9.94 IPS |
|
|
Machine Translation (HP)
|
100% |
536
9.23 IPS |
|
|
Machine Translation (Q)
|
57% |
426
10.4 IPS |
