Samsung Galaxy S24 Ultra
Geekbench AI Score
441
Single Precision Score
437
Half Precision Score
938
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 16 2025 08:10 PM |
| 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% |
314
58.4 IPS |
|
|
Image Classification (HP)
|
100% |
312
58.0 IPS |
|
|
Image Classification (Q)
|
99% |
814
151.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
397
6.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
398
6.45 IPS |
|
|
Image Segmentation (Q)
|
98% |
800
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
545
0.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
532
0.62 IPS |
|
|
Pose Estimation (Q)
|
98% |
1722
2.02 IPS |
|
|
Object Detection (SP)
|
100% |
254
20.1 IPS |
|
|
Object Detection (HP)
|
100% |
256
20.3 IPS |
|
|
Object Detection (Q)
|
87% |
697
55.9 IPS |
|
|
Face Detection (SP)
|
100% |
646
7.68 IPS |
|
|
Face Detection (HP)
|
100% |
650
7.72 IPS |
|
|
Face Detection (Q)
|
97% |
1445
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
559
4.31 IPS |
|
|
Depth Estimation (HP)
|
99% |
538
4.15 IPS |
|
|
Depth Estimation (Q)
|
64% |
1141
10.4 IPS |
|
|
Style Transfer (SP)
|
100% |
820
1.05 IPS |
|
|
Style Transfer (HP)
|
100% |
807
1.04 IPS |
|
|
Style Transfer (Q)
|
98% |
1913
2.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
279
10.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
277
10.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
909
33.7 IPS |
|
|
Text Classification (SP)
|
100% |
333
444.6 IPS |
|
|
Text Classification (HP)
|
100% |
334
445.2 IPS |
|
|
Text Classification (Q)
|
91% |
541
727.7 IPS |
|
|
Machine Translation (SP)
|
100% |
592
10.2 IPS |
|
|
Machine Translation (HP)
|
100% |
576
9.93 IPS |
|
|
Machine Translation (Q)
|
57% |
437
10.7 IPS |
