Samsung Galaxy S24 Ultra
Geekbench AI Score
520
Single Precision Score
22591
Half Precision Score
51418
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 05 2025 10:37 PM |
| Views | 9 |
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% |
310
57.7 IPS |
|
|
Image Classification (HP)
|
100% |
18229
3.39 KIPS |
|
|
Image Classification (Q)
|
97% |
41757
7.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
394
6.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
11062
179.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
31486
512.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
545
0.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
100735
117.5 IPS |
|
|
Pose Estimation (Q)
|
98% |
398052
465.9 IPS |
|
|
Object Detection (SP)
|
100% |
307
24.4 IPS |
|
|
Object Detection (HP)
|
100% |
16432
1.30 KIPS |
|
|
Object Detection (Q)
|
86% |
20467
1.65 KIPS |
|
|
Face Detection (SP)
|
100% |
762
9.06 IPS |
|
|
Face Detection (HP)
|
100% |
35531
422.2 IPS |
|
|
Face Detection (Q)
|
97% |
127917
1.53 KIPS |
|
|
Depth Estimation (SP)
|
100% |
690
5.31 IPS |
|
|
Depth Estimation (HP)
|
99% |
64581
497.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
118099
1.11 KIPS |
|
|
Style Transfer (SP)
|
100% |
1094
1.41 IPS |
|
|
Style Transfer (HP)
|
98% |
85453
110.2 IPS |
|
|
Style Transfer (Q)
|
98% |
422865
545.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
368
13.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
45124
1.67 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103525
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
460
614.1 IPS |
|
|
Text Classification (HP)
|
100% |
3109
4.15 KIPS |
|
|
Text Classification (Q)
|
93% |
6926
9.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
728
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
3772
65.0 IPS |
|
|
Machine Translation (Q)
|
55% |
2633
69.0 IPS |
