Samsung Galaxy S24 Ultra
Geekbench AI Score
490
Single Precision Score
22515
Half Precision Score
51257
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 22 2025 03:17 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
312
58.0 IPS |
|
|
Image Classification (HP)
|
100% |
18305
3.40 KIPS |
|
|
Image Classification (Q)
|
97% |
42114
7.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
391
6.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
10944
177.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
31500
512.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
522
0.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
100277
117.0 IPS |
|
|
Pose Estimation (Q)
|
98% |
398334
466.2 IPS |
|
|
Object Detection (SP)
|
100% |
290
23.0 IPS |
|
|
Object Detection (HP)
|
100% |
16462
1.31 KIPS |
|
|
Object Detection (Q)
|
86% |
20500
1.65 KIPS |
|
|
Face Detection (SP)
|
100% |
705
8.38 IPS |
|
|
Face Detection (HP)
|
100% |
35234
418.7 IPS |
|
|
Face Detection (Q)
|
97% |
126695
1.51 KIPS |
|
|
Depth Estimation (SP)
|
100% |
629
4.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
64041
493.4 IPS |
|
|
Depth Estimation (Q)
|
63% |
116212
1.09 KIPS |
|
|
Style Transfer (SP)
|
100% |
1005
1.29 IPS |
|
|
Style Transfer (HP)
|
98% |
85512
110.3 IPS |
|
|
Style Transfer (Q)
|
98% |
422545
544.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
331
12.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
46050
1.70 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103617
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
430
574.0 IPS |
|
|
Text Classification (HP)
|
100% |
3097
4.13 KIPS |
|
|
Text Classification (Q)
|
93% |
6893
9.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
682
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
3680
63.4 IPS |
|
|
Machine Translation (Q)
|
55% |
2601
68.1 IPS |
