Samsung Galaxy S24 Ultra
Geekbench AI Score
449
Single Precision Score
438
Half Precision Score
986
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Beamish |
| Upload Date | October 28 2025 06:18 PM |
| Views | 11 |
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% |
307
57.0 IPS |
|
|
Image Classification (HP)
|
100% |
308
57.2 IPS |
|
|
Image Classification (Q)
|
99% |
800
149.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
388
6.30 IPS |
|
|
Image Segmentation (HP)
|
100% |
394
6.38 IPS |
|
|
Image Segmentation (Q)
|
98% |
804
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
534
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
526
0.61 IPS |
|
|
Pose Estimation (Q)
|
98% |
1796
2.10 IPS |
|
|
Object Detection (SP)
|
100% |
268
21.2 IPS |
|
|
Object Detection (HP)
|
100% |
265
21.0 IPS |
|
|
Object Detection (Q)
|
87% |
787
63.1 IPS |
|
|
Face Detection (SP)
|
100% |
685
8.14 IPS |
|
|
Face Detection (HP)
|
100% |
643
7.64 IPS |
|
|
Face Detection (Q)
|
97% |
1455
17.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
575
4.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
545
4.20 IPS |
|
|
Depth Estimation (Q)
|
64% |
1258
11.4 IPS |
|
|
Style Transfer (SP)
|
100% |
873
1.12 IPS |
|
|
Style Transfer (HP)
|
100% |
796
1.02 IPS |
|
|
Style Transfer (Q)
|
98% |
2002
2.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
283
10.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
283
10.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
943
34.9 IPS |
|
|
Text Classification (SP)
|
100% |
340
454.2 IPS |
|
|
Text Classification (HP)
|
100% |
341
455.7 IPS |
|
|
Text Classification (Q)
|
91% |
601
807.7 IPS |
|
|
Machine Translation (SP)
|
100% |
592
10.2 IPS |
|
|
Machine Translation (HP)
|
100% |
577
9.94 IPS |
|
|
Machine Translation (Q)
|
57% |
461
11.3 IPS |
