Samsung Galaxy S24 Ultra
Geekbench AI Score
387
Single Precision Score
373
Half Precision Score
823
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 10 2025 01:12 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% |
306
56.9 IPS |
|
|
Image Classification (HP)
|
100% |
302
56.2 IPS |
|
|
Image Classification (Q)
|
99% |
786
146.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
384
6.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
389
6.31 IPS |
|
|
Image Segmentation (Q)
|
98% |
772
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
530
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
367
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1390
1.63 IPS |
|
|
Object Detection (SP)
|
100% |
199
15.8 IPS |
|
|
Object Detection (HP)
|
100% |
199
15.8 IPS |
|
|
Object Detection (Q)
|
87% |
557
44.7 IPS |
|
|
Face Detection (SP)
|
100% |
518
6.16 IPS |
|
|
Face Detection (HP)
|
100% |
523
6.22 IPS |
|
|
Face Detection (Q)
|
97% |
1143
13.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
454
3.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
456
3.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
1013
9.19 IPS |
|
|
Style Transfer (SP)
|
100% |
745
0.96 IPS |
|
|
Style Transfer (HP)
|
100% |
743
0.96 IPS |
|
|
Style Transfer (Q)
|
98% |
1776
2.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
242
8.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
242
8.92 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
792
29.4 IPS |
|
|
Text Classification (SP)
|
100% |
294
391.8 IPS |
|
|
Text Classification (HP)
|
100% |
292
389.3 IPS |
|
|
Text Classification (Q)
|
91% |
477
641.6 IPS |
|
|
Machine Translation (SP)
|
100% |
491
8.46 IPS |
|
|
Machine Translation (HP)
|
100% |
490
8.45 IPS |
|
|
Machine Translation (Q)
|
57% |
393
9.60 IPS |
