Samsung Galaxy S24 Ultra
Geekbench AI Score
2222
Single Precision Score
2272
Half Precision Score
3320
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 21 2024 10:29 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-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% |
2053
381.7 IPS |
|
|
Image Classification (HP)
|
100% |
2430
451.9 IPS |
|
|
Image Classification (Q)
|
100% |
2910
541.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2663
43.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2620
42.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
4267
69.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4056
4.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
4053
4.73 IPS |
|
|
Pose Estimation (Q)
|
84% |
7564
8.97 IPS |
|
|
Object Detection (SP)
|
98% |
1244
99.0 IPS |
|
|
Object Detection (HP)
|
98% |
1409
112.1 IPS |
|
|
Object Detection (Q)
|
83% |
1763
142.4 IPS |
|
|
Face Detection (SP)
|
100% |
2813
33.4 IPS |
|
|
Face Detection (HP)
|
100% |
2753
32.7 IPS |
|
|
Face Detection (Q)
|
95% |
4311
51.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2682
20.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2674
20.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5359
49.1 IPS |
|
|
Style Transfer (SP)
|
89% |
8123
10.5 IPS |
|
|
Style Transfer (HP)
|
89% |
8410
10.9 IPS |
|
|
Style Transfer (Q)
|
98% |
15823
20.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1615
59.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1665
61.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3779
140.0 IPS |
|
|
Text Classification (SP)
|
100% |
714
953.5 IPS |
|
|
Text Classification (HP)
|
99% |
660
881.3 IPS |
|
|
Text Classification (Q)
|
88% |
1008
1.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
1508
26.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1486
25.6 IPS |
|
|
Machine Translation (Q)
|
50% |
707
25.1 IPS |
