Samsung Galaxy S24 Ultra
Geekbench AI Score
2406
Single Precision Score
2349
Half Precision Score
3653
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 04 2025 04:07 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928B |
| 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% |
1727
321.1 IPS |
|
|
Image Classification (HP)
|
100% |
1776
330.2 IPS |
|
|
Image Classification (Q)
|
100% |
3061
569.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2212
35.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2253
36.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
3518
57.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4076
4.76 IPS |
|
|
Pose Estimation (HP)
|
100% |
3603
4.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
8395
9.96 IPS |
|
|
Object Detection (SP)
|
98% |
1787
142.2 IPS |
|
|
Object Detection (HP)
|
98% |
1785
142.0 IPS |
|
|
Object Detection (Q)
|
83% |
2588
209.0 IPS |
|
|
Face Detection (SP)
|
100% |
3450
41.0 IPS |
|
|
Face Detection (HP)
|
100% |
3436
40.8 IPS |
|
|
Face Detection (Q)
|
95% |
5666
67.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
3547
27.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3525
27.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
5770
52.9 IPS |
|
|
Style Transfer (SP)
|
89% |
8674
11.3 IPS |
|
|
Style Transfer (HP)
|
89% |
8681
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16746
21.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1781
65.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1762
65.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4248
157.4 IPS |
|
|
Text Classification (SP)
|
100% |
781
1.04 KIPS |
|
|
Text Classification (HP)
|
99% |
776
1.04 KIPS |
|
|
Text Classification (Q)
|
88% |
1189
1.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
1585
27.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1385
23.9 IPS |
|
|
Machine Translation (Q)
|
50% |
655
23.2 IPS |
