Samsung Galaxy S24 Ultra
Geekbench AI Score
428
Single Precision Score
418
Half Precision Score
939
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | gundamf90 |
| Upload Date | August 18 2024 02:23 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S9280 |
| 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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
300
55.7 IPS |
|
|
Image Classification (HP)
|
100% |
280
52.0 IPS |
|
|
Image Classification (Q)
|
97% |
762
142.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
355
5.76 IPS |
|
|
Image Segmentation (HP)
|
100% |
356
5.78 IPS |
|
|
Image Segmentation (Q)
|
98% |
747
12.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
469
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
412
0.48 IPS |
|
|
Pose Estimation (Q)
|
98% |
1532
1.79 IPS |
|
|
Object Detection (SP)
|
100% |
252
20.0 IPS |
|
|
Object Detection (HP)
|
100% |
258
20.5 IPS |
|
|
Object Detection (Q)
|
89% |
710
56.8 IPS |
|
|
Face Detection (SP)
|
100% |
621
7.38 IPS |
|
|
Face Detection (HP)
|
100% |
620
7.36 IPS |
|
|
Face Detection (Q)
|
97% |
1401
16.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
549
4.23 IPS |
|
|
Depth Estimation (HP)
|
100% |
530
4.09 IPS |
|
|
Depth Estimation (Q)
|
73% |
1302
10.7 IPS |
|
|
Style Transfer (SP)
|
100% |
816
1.05 IPS |
|
|
Style Transfer (HP)
|
100% |
814
1.05 IPS |
|
|
Style Transfer (Q)
|
98% |
1928
2.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
276
10.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
281
10.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
931
34.5 IPS |
|
|
Text Classification (SP)
|
100% |
351
469.2 IPS |
|
|
Text Classification (HP)
|
100% |
349
466.5 IPS |
|
|
Text Classification (Q)
|
91% |
560
752.7 IPS |
|
|
Machine Translation (SP)
|
100% |
610
10.5 IPS |
|
|
Machine Translation (HP)
|
100% |
593
10.2 IPS |
|
|
Machine Translation (Q)
|
57% |
472
11.5 IPS |
