Samsung Galaxy S24 Ultra
Geekbench AI Score
310
Single Precision Score
310
Half Precision Score
686
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | tobbyng |
| Upload Date | December 27 2025 01:34 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S9280 |
| 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% |
181
33.6 IPS |
|
|
Image Classification (HP)
|
100% |
180
33.5 IPS |
|
|
Image Classification (Q)
|
99% |
463
86.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
235
3.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
237
3.84 IPS |
|
|
Image Segmentation (Q)
|
98% |
470
7.64 IPS |
|
|
Pose Estimation (SP)
|
100% |
337
0.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
337
0.39 IPS |
|
|
Pose Estimation (Q)
|
98% |
1245
1.46 IPS |
|
|
Object Detection (SP)
|
100% |
183
14.5 IPS |
|
|
Object Detection (HP)
|
100% |
182
14.4 IPS |
|
|
Object Detection (Q)
|
87% |
505
40.5 IPS |
|
|
Face Detection (SP)
|
100% |
461
5.48 IPS |
|
|
Face Detection (HP)
|
100% |
466
5.54 IPS |
|
|
Face Detection (Q)
|
97% |
1043
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
408
3.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
413
3.18 IPS |
|
|
Depth Estimation (Q)
|
64% |
938
8.51 IPS |
|
|
Style Transfer (SP)
|
100% |
663
0.85 IPS |
|
|
Style Transfer (HP)
|
100% |
667
0.86 IPS |
|
|
Style Transfer (Q)
|
98% |
1619
2.09 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
216
7.96 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
215
7.93 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
716
26.5 IPS |
|
|
Text Classification (SP)
|
100% |
268
358.1 IPS |
|
|
Text Classification (HP)
|
100% |
269
358.9 IPS |
|
|
Text Classification (Q)
|
91% |
428
575.5 IPS |
|
|
Machine Translation (SP)
|
100% |
435
7.50 IPS |
|
|
Machine Translation (HP)
|
100% |
434
7.47 IPS |
|
|
Machine Translation (Q)
|
57% |
352
8.60 IPS |
