Samsung Galaxy S24 Ultra
Geekbench AI Score
416
Single Precision Score
400
Half Precision Score
890
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | rodrigo_rl |
| Upload Date | June 16 2025 06:46 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
290
53.9 IPS |
|
|
Image Classification (HP)
|
100% |
287
53.4 IPS |
|
|
Image Classification (Q)
|
99% |
757
141.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
369
5.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
366
5.94 IPS |
|
|
Image Segmentation (Q)
|
98% |
732
11.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
456
0.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
401
0.47 IPS |
|
|
Pose Estimation (Q)
|
98% |
1557
1.82 IPS |
|
|
Object Detection (SP)
|
100% |
235
18.6 IPS |
|
|
Object Detection (HP)
|
100% |
236
18.7 IPS |
|
|
Object Detection (Q)
|
87% |
665
53.4 IPS |
|
|
Face Detection (SP)
|
100% |
611
7.26 IPS |
|
|
Face Detection (HP)
|
100% |
588
6.99 IPS |
|
|
Face Detection (Q)
|
97% |
1282
15.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
523
4.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
501
3.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
1115
10.1 IPS |
|
|
Style Transfer (SP)
|
100% |
797
1.02 IPS |
|
|
Style Transfer (HP)
|
100% |
732
0.94 IPS |
|
|
Style Transfer (Q)
|
98% |
1920
2.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
281
10.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
280
10.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
889
32.9 IPS |
|
|
Text Classification (SP)
|
100% |
327
436.8 IPS |
|
|
Text Classification (HP)
|
100% |
326
435.6 IPS |
|
|
Text Classification (Q)
|
91% |
530
711.9 IPS |
|
|
Machine Translation (SP)
|
100% |
579
9.98 IPS |
|
|
Machine Translation (HP)
|
100% |
546
9.40 IPS |
|
|
Machine Translation (Q)
|
57% |
421
10.3 IPS |
