Samsung Galaxy S24 Ultra
Geekbench AI Score
387
Single Precision Score
389
Half Precision Score
882
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | tobbyng |
| Upload Date | December 27 2025 02:01 AM |
| Views | 8 |
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% |
132
24.5 IPS |
|
|
Image Classification (HP)
|
100% |
113
21.0 IPS |
|
|
Image Classification (Q)
|
99% |
320
59.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
167
2.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
177
2.87 IPS |
|
|
Image Segmentation (Q)
|
98% |
348
5.66 IPS |
|
|
Pose Estimation (SP)
|
100% |
420
0.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
474
0.55 IPS |
|
|
Pose Estimation (Q)
|
98% |
1805
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
267
21.2 IPS |
|
|
Object Detection (HP)
|
100% |
272
21.6 IPS |
|
|
Object Detection (Q)
|
87% |
776
62.3 IPS |
|
|
Face Detection (SP)
|
100% |
692
8.22 IPS |
|
|
Face Detection (HP)
|
100% |
685
8.14 IPS |
|
|
Face Detection (Q)
|
97% |
1610
19.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
575
4.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
586
4.51 IPS |
|
|
Depth Estimation (Q)
|
64% |
1375
12.5 IPS |
|
|
Style Transfer (SP)
|
100% |
943
1.21 IPS |
|
|
Style Transfer (HP)
|
100% |
934
1.20 IPS |
|
|
Style Transfer (Q)
|
98% |
2318
2.99 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
321
11.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
322
11.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1067
39.5 IPS |
|
|
Text Classification (SP)
|
100% |
396
529.1 IPS |
|
|
Text Classification (HP)
|
100% |
401
534.8 IPS |
|
|
Text Classification (Q)
|
91% |
645
866.6 IPS |
|
|
Machine Translation (SP)
|
100% |
646
11.1 IPS |
|
|
Machine Translation (HP)
|
100% |
652
11.2 IPS |
|
|
Machine Translation (Q)
|
57% |
518
12.6 IPS |
