Samsung Galaxy S24 Ultra
Geekbench AI Score
388
Single Precision Score
376
Half Precision Score
827
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 10 2025 04:20 AM |
| 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% |
302
56.2 IPS |
|
|
Image Classification (HP)
|
100% |
299
55.5 IPS |
|
|
Image Classification (Q)
|
99% |
792
147.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
386
6.25 IPS |
|
|
Image Segmentation (HP)
|
100% |
387
6.28 IPS |
|
|
Image Segmentation (Q)
|
98% |
785
12.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
508
0.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
376
0.44 IPS |
|
|
Pose Estimation (Q)
|
98% |
1429
1.67 IPS |
|
|
Object Detection (SP)
|
100% |
207
16.4 IPS |
|
|
Object Detection (HP)
|
100% |
207
16.4 IPS |
|
|
Object Detection (Q)
|
87% |
578
46.4 IPS |
|
|
Face Detection (SP)
|
100% |
532
6.33 IPS |
|
|
Face Detection (HP)
|
100% |
538
6.39 IPS |
|
|
Face Detection (Q)
|
97% |
1112
13.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
454
3.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
458
3.53 IPS |
|
|
Depth Estimation (Q)
|
64% |
1014
9.20 IPS |
|
|
Style Transfer (SP)
|
100% |
747
0.96 IPS |
|
|
Style Transfer (HP)
|
100% |
744
0.96 IPS |
|
|
Style Transfer (Q)
|
98% |
1777
2.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
243
8.99 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
242
8.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
788
29.2 IPS |
|
|
Text Classification (SP)
|
100% |
296
394.5 IPS |
|
|
Text Classification (HP)
|
100% |
292
389.9 IPS |
|
|
Text Classification (Q)
|
91% |
477
640.8 IPS |
|
|
Machine Translation (SP)
|
100% |
490
8.45 IPS |
|
|
Machine Translation (HP)
|
100% |
496
8.55 IPS |
|
|
Machine Translation (Q)
|
57% |
391
9.55 IPS |
