Samsung Galaxy S24 Ultra
Geekbench AI Score
484
Single Precision Score
472
Half Precision Score
1058
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Beamish |
| Upload Date | November 21 2025 09:05 AM |
| Views | 4 |
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-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% |
301
56.0 IPS |
|
|
Image Classification (HP)
|
100% |
301
56.0 IPS |
|
|
Image Classification (Q)
|
99% |
780
145.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
379
6.14 IPS |
|
|
Image Segmentation (HP)
|
100% |
380
6.16 IPS |
|
|
Image Segmentation (Q)
|
98% |
779
12.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
512
0.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
479
0.56 IPS |
|
|
Pose Estimation (Q)
|
98% |
1914
2.24 IPS |
|
|
Object Detection (SP)
|
100% |
285
22.6 IPS |
|
|
Object Detection (HP)
|
100% |
274
21.7 IPS |
|
|
Object Detection (Q)
|
87% |
782
62.7 IPS |
|
|
Face Detection (SP)
|
100% |
688
8.18 IPS |
|
|
Face Detection (HP)
|
100% |
696
8.26 IPS |
|
|
Face Detection (Q)
|
97% |
1559
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
633
4.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
587
4.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
1463
13.3 IPS |
|
|
Style Transfer (SP)
|
100% |
946
1.22 IPS |
|
|
Style Transfer (HP)
|
100% |
939
1.21 IPS |
|
|
Style Transfer (Q)
|
98% |
2403
3.10 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
346
12.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
329
12.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1035
38.3 IPS |
|
|
Text Classification (SP)
|
100% |
428
571.7 IPS |
|
|
Text Classification (HP)
|
100% |
428
571.7 IPS |
|
|
Text Classification (Q)
|
91% |
675
907.5 IPS |
|
|
Machine Translation (SP)
|
100% |
697
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
680
11.7 IPS |
|
|
Machine Translation (Q)
|
57% |
506
12.4 IPS |
