Samsung Galaxy S24 Ultra
Geekbench AI Score
463
Single Precision Score
466
Half Precision Score
1088
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | August 16 2024 05:32 AM |
| Views | 3 |
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-S928N |
| 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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
281
52.3 IPS |
|
|
Image Classification (HP)
|
100% |
280
52.2 IPS |
|
|
Image Classification (Q)
|
97% |
745
139.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
345
5.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
347
5.63 IPS |
|
|
Image Segmentation (Q)
|
98% |
738
12.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
461
0.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
467
0.55 IPS |
|
|
Pose Estimation (Q)
|
98% |
1832
2.14 IPS |
|
|
Object Detection (SP)
|
100% |
275
21.8 IPS |
|
|
Object Detection (HP)
|
100% |
280
22.2 IPS |
|
|
Object Detection (Q)
|
89% |
808
64.7 IPS |
|
|
Face Detection (SP)
|
100% |
677
8.04 IPS |
|
|
Face Detection (HP)
|
100% |
682
8.11 IPS |
|
|
Face Detection (Q)
|
97% |
1669
19.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
607
4.67 IPS |
|
|
Depth Estimation (HP)
|
100% |
598
4.61 IPS |
|
|
Depth Estimation (Q)
|
73% |
1606
13.1 IPS |
|
|
Style Transfer (SP)
|
100% |
987
1.27 IPS |
|
|
Style Transfer (HP)
|
100% |
991
1.27 IPS |
|
|
Style Transfer (Q)
|
98% |
2423
3.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
317
11.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
322
11.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1100
40.7 IPS |
|
|
Text Classification (SP)
|
100% |
429
572.5 IPS |
|
|
Text Classification (HP)
|
100% |
435
580.4 IPS |
|
|
Text Classification (Q)
|
91% |
708
951.6 IPS |
|
|
Machine Translation (SP)
|
100% |
678
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
674
11.6 IPS |
|
|
Machine Translation (Q)
|
57% |
565
13.8 IPS |
