Samsung Galaxy S24 Ultra
Geekbench AI Score
2379
Single Precision Score
2363
Half Precision Score
3329
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | curranc |
| Upload Date | June 12 2025 07:47 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
2035
378.4 IPS |
|
|
Image Classification (HP)
|
100% |
1984
368.9 IPS |
|
|
Image Classification (Q)
|
100% |
1712
318.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2698
43.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2661
43.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
4345
70.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3883
4.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3631
4.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
8363
9.92 IPS |
|
|
Object Detection (SP)
|
98% |
1774
141.1 IPS |
|
|
Object Detection (HP)
|
98% |
1772
141.0 IPS |
|
|
Object Detection (Q)
|
83% |
2341
189.1 IPS |
|
|
Face Detection (SP)
|
100% |
3437
40.8 IPS |
|
|
Face Detection (HP)
|
100% |
3443
40.9 IPS |
|
|
Face Detection (Q)
|
95% |
5687
67.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
3516
27.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3450
26.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5783
53.0 IPS |
|
|
Style Transfer (SP)
|
89% |
8751
11.4 IPS |
|
|
Style Transfer (HP)
|
89% |
8760
11.4 IPS |
|
|
Style Transfer (Q)
|
98% |
15008
19.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1503
55.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1648
60.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3777
139.9 IPS |
|
|
Text Classification (SP)
|
100% |
690
920.4 IPS |
|
|
Text Classification (HP)
|
99% |
684
912.3 IPS |
|
|
Text Classification (Q)
|
88% |
940
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
1402
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1363
23.5 IPS |
|
|
Machine Translation (Q)
|
50% |
656
23.3 IPS |
