Samsung Galaxy S24 Ultra
Geekbench AI Score
2541
Single Precision Score
2501
Half Precision Score
3712
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 05 2025 06:22 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% |
2132
396.5 IPS |
|
|
Image Classification (HP)
|
100% |
2236
415.9 IPS |
|
|
Image Classification (Q)
|
100% |
3542
658.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2649
42.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2663
43.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4446
72.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4306
5.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
4125
4.81 IPS |
|
|
Pose Estimation (Q)
|
84% |
7889
9.36 IPS |
|
|
Object Detection (SP)
|
98% |
1756
139.8 IPS |
|
|
Object Detection (HP)
|
98% |
1736
138.1 IPS |
|
|
Object Detection (Q)
|
83% |
2530
204.4 IPS |
|
|
Face Detection (SP)
|
100% |
3674
43.7 IPS |
|
|
Face Detection (HP)
|
100% |
3680
43.7 IPS |
|
|
Face Detection (Q)
|
95% |
5794
69.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3780
29.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3699
28.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
5899
54.0 IPS |
|
|
Style Transfer (SP)
|
89% |
8887
11.5 IPS |
|
|
Style Transfer (HP)
|
89% |
8416
10.9 IPS |
|
|
Style Transfer (Q)
|
98% |
15625
20.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1696
62.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1722
63.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3958
146.7 IPS |
|
|
Text Classification (SP)
|
100% |
754
1.01 KIPS |
|
|
Text Classification (HP)
|
99% |
687
916.4 IPS |
|
|
Text Classification (Q)
|
88% |
1059
1.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1669
28.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1663
28.6 IPS |
|
|
Machine Translation (Q)
|
50% |
706
25.1 IPS |
