Samsung Galaxy S24 Ultra
Geekbench AI Score
492
Single Precision Score
22610
Half Precision Score
51409
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 10 2025 02:36 PM |
| Views | 4 |
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% |
314
58.4 IPS |
|
|
Image Classification (HP)
|
100% |
18150
3.38 KIPS |
|
|
Image Classification (Q)
|
97% |
41865
7.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
398
6.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
11006
178.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
31597
513.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
525
0.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
99293
115.9 IPS |
|
|
Pose Estimation (Q)
|
98% |
398803
466.8 IPS |
|
|
Object Detection (SP)
|
100% |
284
22.5 IPS |
|
|
Object Detection (HP)
|
100% |
16509
1.31 KIPS |
|
|
Object Detection (Q)
|
86% |
20508
1.65 KIPS |
|
|
Face Detection (SP)
|
100% |
724
8.60 IPS |
|
|
Face Detection (HP)
|
100% |
35523
422.1 IPS |
|
|
Face Detection (Q)
|
97% |
127447
1.52 KIPS |
|
|
Depth Estimation (SP)
|
100% |
634
4.88 IPS |
|
|
Depth Estimation (HP)
|
99% |
64601
497.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
117764
1.10 KIPS |
|
|
Style Transfer (SP)
|
100% |
1006
1.29 IPS |
|
|
Style Transfer (HP)
|
98% |
85551
110.3 IPS |
|
|
Style Transfer (Q)
|
98% |
422623
545.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
332
12.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
46107
1.70 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103519
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
424
566.0 IPS |
|
|
Text Classification (HP)
|
100% |
3098
4.13 KIPS |
|
|
Text Classification (Q)
|
93% |
6891
9.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
689
11.9 IPS |
|
|
Machine Translation (HP)
|
100% |
3803
65.5 IPS |
|
|
Machine Translation (Q)
|
55% |
2634
69.0 IPS |
