Samsung Galaxy S24 Ultra [A15] Samsung Galaxy S24 Ultra
Geekbench AI Score
2841
Single Precision Score
2803
Half Precision Score
4197
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | NienorGT |
| Upload Date | May 01 2025 02:27 AM |
| Views | 2 |
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-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% |
2434
452.7 IPS |
|
|
Image Classification (HP)
|
100% |
2436
453.0 IPS |
|
|
Image Classification (Q)
|
100% |
2077
386.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2621
42.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2727
44.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4198
68.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4422
5.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
4090
4.77 IPS |
|
|
Pose Estimation (Q)
|
84% |
9870
11.7 IPS |
|
|
Object Detection (SP)
|
98% |
2198
174.9 IPS |
|
|
Object Detection (HP)
|
98% |
1894
150.7 IPS |
|
|
Object Detection (Q)
|
83% |
3192
257.9 IPS |
|
|
Face Detection (SP)
|
100% |
4085
48.5 IPS |
|
|
Face Detection (HP)
|
100% |
4071
48.4 IPS |
|
|
Face Detection (Q)
|
95% |
7382
88.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
4234
32.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4278
33.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
6874
63.0 IPS |
|
|
Style Transfer (SP)
|
89% |
10020
13.0 IPS |
|
|
Style Transfer (HP)
|
89% |
10159
13.2 IPS |
|
|
Style Transfer (Q)
|
98% |
20460
26.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2072
76.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2085
77.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4800
177.9 IPS |
|
|
Text Classification (SP)
|
100% |
843
1.13 KIPS |
|
|
Text Classification (HP)
|
99% |
898
1.20 KIPS |
|
|
Text Classification (Q)
|
88% |
1405
1.90 KIPS |
|
|
Machine Translation (SP)
|
100% |
1828
31.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1761
30.3 IPS |
|
|
Machine Translation (Q)
|
50% |
882
31.3 IPS |
