Samsung Galaxy S24 Ultra
Geekbench AI Score
2792
Single Precision Score
2953
Half Precision Score
4529
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Wilhelm |
| Upload Date | January 31 2025 05:47 PM |
| Views | 5 |
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% |
1474
274.1 IPS |
|
|
Image Classification (HP)
|
100% |
2458
457.2 IPS |
|
|
Image Classification (Q)
|
100% |
2856
531.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2821
45.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2809
45.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
4377
71.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4586
5.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
4354
5.08 IPS |
|
|
Pose Estimation (Q)
|
84% |
10240
12.1 IPS |
|
|
Object Detection (SP)
|
98% |
2031
161.6 IPS |
|
|
Object Detection (HP)
|
98% |
2220
176.7 IPS |
|
|
Object Detection (Q)
|
83% |
3188
257.5 IPS |
|
|
Face Detection (SP)
|
100% |
4256
50.6 IPS |
|
|
Face Detection (HP)
|
100% |
4251
50.5 IPS |
|
|
Face Detection (Q)
|
95% |
7934
94.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4357
33.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4290
33.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
7601
69.6 IPS |
|
|
Style Transfer (SP)
|
89% |
10710
13.9 IPS |
|
|
Style Transfer (HP)
|
89% |
10670
13.9 IPS |
|
|
Style Transfer (Q)
|
98% |
20475
26.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2096
77.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2217
81.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5406
200.3 IPS |
|
|
Text Classification (SP)
|
100% |
976
1.30 KIPS |
|
|
Text Classification (HP)
|
99% |
991
1.32 KIPS |
|
|
Text Classification (Q)
|
88% |
1410
1.90 KIPS |
|
|
Machine Translation (SP)
|
100% |
1832
31.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1773
30.5 IPS |
|
|
Machine Translation (Q)
|
50% |
946
33.6 IPS |
