Samsung Galaxy S24 Ultra
Geekbench AI Score
401
Single Precision Score
380
Half Precision Score
837
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 16 2025 09:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928U1 |
| 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% |
310
57.7 IPS |
|
|
Image Classification (HP)
|
100% |
308
57.3 IPS |
|
|
Image Classification (Q)
|
99% |
807
150.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
391
6.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
392
6.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
791
12.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
536
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
368
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1442
1.69 IPS |
|
|
Object Detection (SP)
|
100% |
219
17.4 IPS |
|
|
Object Detection (HP)
|
100% |
206
16.4 IPS |
|
|
Object Detection (Q)
|
87% |
599
48.1 IPS |
|
|
Face Detection (SP)
|
100% |
566
6.73 IPS |
|
|
Face Detection (HP)
|
100% |
524
6.23 IPS |
|
|
Face Detection (Q)
|
97% |
1148
13.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
468
3.61 IPS |
|
|
Depth Estimation (HP)
|
99% |
459
3.54 IPS |
|
|
Depth Estimation (Q)
|
64% |
1019
9.24 IPS |
|
|
Style Transfer (SP)
|
100% |
749
0.96 IPS |
|
|
Style Transfer (HP)
|
100% |
743
0.96 IPS |
|
|
Style Transfer (Q)
|
98% |
1775
2.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
250
9.23 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
248
9.16 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
793
29.4 IPS |
|
|
Text Classification (SP)
|
100% |
290
386.8 IPS |
|
|
Text Classification (HP)
|
100% |
291
388.0 IPS |
|
|
Text Classification (Q)
|
91% |
478
642.2 IPS |
|
|
Machine Translation (SP)
|
100% |
537
9.25 IPS |
|
|
Machine Translation (HP)
|
100% |
534
9.21 IPS |
|
|
Machine Translation (Q)
|
57% |
392
9.58 IPS |
