Samsung Galaxy S24 Ultra
Geekbench AI Score
2615
Single Precision Score
2617
Half Precision Score
4000
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | PC2025 |
| Upload Date | January 12 2025 11:44 PM |
| Views | 2 |
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-S928W |
| 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% |
2045
380.3 IPS |
|
|
Image Classification (HP)
|
100% |
2418
449.7 IPS |
|
|
Image Classification (Q)
|
100% |
3526
655.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2825
45.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2788
45.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4365
71.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4552
5.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
4401
5.13 IPS |
|
|
Pose Estimation (Q)
|
84% |
10076
12.0 IPS |
|
|
Object Detection (SP)
|
98% |
2157
171.7 IPS |
|
|
Object Detection (HP)
|
98% |
2212
176.0 IPS |
|
|
Object Detection (Q)
|
83% |
3317
267.9 IPS |
|
|
Face Detection (SP)
|
100% |
4348
51.7 IPS |
|
|
Face Detection (HP)
|
100% |
3301
39.2 IPS |
|
|
Face Detection (Q)
|
95% |
5667
67.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
3237
25.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3295
25.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
5833
53.4 IPS |
|
|
Style Transfer (SP)
|
89% |
8884
11.5 IPS |
|
|
Style Transfer (HP)
|
89% |
8783
11.4 IPS |
|
|
Style Transfer (Q)
|
98% |
16650
21.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1708
63.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1807
66.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4155
154.0 IPS |
|
|
Text Classification (SP)
|
100% |
769
1.03 KIPS |
|
|
Text Classification (HP)
|
99% |
768
1.03 KIPS |
|
|
Text Classification (Q)
|
88% |
1072
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
1610
27.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1734
29.9 IPS |
|
|
Machine Translation (Q)
|
50% |
832
29.6 IPS |
