Samsung Galaxy S24 Ultra
Geekbench AI Score
485
Single Precision Score
480
Half Precision Score
1057
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 10 2025 01:33 AM |
| Views | 9 |
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% |
311
57.9 IPS |
|
|
Image Classification (HP)
|
100% |
316
58.7 IPS |
|
|
Image Classification (Q)
|
99% |
817
152.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
399
6.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
404
6.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
810
13.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
557
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
542
0.63 IPS |
|
|
Pose Estimation (Q)
|
98% |
2089
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
298
23.6 IPS |
|
|
Object Detection (HP)
|
100% |
300
23.8 IPS |
|
|
Object Detection (Q)
|
87% |
852
68.3 IPS |
|
|
Face Detection (SP)
|
100% |
750
8.91 IPS |
|
|
Face Detection (HP)
|
100% |
759
9.02 IPS |
|
|
Face Detection (Q)
|
97% |
1742
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
658
5.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
655
5.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
1287
11.7 IPS |
|
|
Style Transfer (SP)
|
100% |
932
1.20 IPS |
|
|
Style Transfer (HP)
|
100% |
878
1.13 IPS |
|
|
Style Transfer (Q)
|
98% |
2140
2.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
305
11.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
307
11.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1035
38.3 IPS |
|
|
Text Classification (SP)
|
100% |
378
504.3 IPS |
|
|
Text Classification (HP)
|
100% |
379
505.9 IPS |
|
|
Text Classification (Q)
|
91% |
620
832.8 IPS |
|
|
Machine Translation (SP)
|
100% |
664
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
624
10.7 IPS |
|
|
Machine Translation (Q)
|
57% |
483
11.8 IPS |
