Samsung Galaxy S24 Ultra
Geekbench AI Score
387
Single Precision Score
381
Half Precision Score
844
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 10 2025 04:49 AM |
| Views | 2 |
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% |
303
56.3 IPS |
|
|
Image Classification (HP)
|
100% |
303
56.3 IPS |
|
|
Image Classification (Q)
|
99% |
791
147.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
384
6.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
388
6.29 IPS |
|
|
Image Segmentation (Q)
|
98% |
783
12.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
534
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
367
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1381
1.62 IPS |
|
|
Object Detection (SP)
|
100% |
200
15.9 IPS |
|
|
Object Detection (HP)
|
100% |
201
16.0 IPS |
|
|
Object Detection (Q)
|
87% |
557
44.7 IPS |
|
|
Face Detection (SP)
|
100% |
516
6.13 IPS |
|
|
Face Detection (HP)
|
100% |
523
6.22 IPS |
|
|
Face Detection (Q)
|
97% |
1155
13.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
455
3.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
457
3.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
1009
9.16 IPS |
|
|
Style Transfer (SP)
|
100% |
745
0.96 IPS |
|
|
Style Transfer (HP)
|
100% |
743
0.96 IPS |
|
|
Style Transfer (Q)
|
98% |
1769
2.28 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
242
8.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
290
10.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1000
37.1 IPS |
|
|
Text Classification (SP)
|
100% |
289
386.4 IPS |
|
|
Text Classification (HP)
|
100% |
291
387.7 IPS |
|
|
Text Classification (Q)
|
91% |
477
640.7 IPS |
|
|
Machine Translation (SP)
|
100% |
505
8.70 IPS |
|
|
Machine Translation (HP)
|
100% |
506
8.72 IPS |
|
|
Machine Translation (Q)
|
57% |
393
9.60 IPS |
