Samsung Galaxy S24 Ultra
Geekbench AI Score
518
Single Precision Score
22666
Half Precision Score
51253
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | August 01 2025 03:24 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
318
59.1 IPS |
|
|
Image Classification (HP)
|
100% |
18449
3.43 KIPS |
|
|
Image Classification (Q)
|
97% |
42065
7.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
412
6.68 IPS |
|
|
Image Segmentation (HP)
|
100% |
11044
179.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
31466
511.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
553
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
100303
117.0 IPS |
|
|
Pose Estimation (Q)
|
98% |
397773
465.6 IPS |
|
|
Object Detection (SP)
|
100% |
304
24.1 IPS |
|
|
Object Detection (HP)
|
100% |
16490
1.31 KIPS |
|
|
Object Detection (Q)
|
86% |
20474
1.65 KIPS |
|
|
Face Detection (SP)
|
100% |
765
9.09 IPS |
|
|
Face Detection (HP)
|
100% |
35122
417.3 IPS |
|
|
Face Detection (Q)
|
97% |
124641
1.49 KIPS |
|
|
Depth Estimation (SP)
|
100% |
679
5.23 IPS |
|
|
Depth Estimation (HP)
|
99% |
64706
498.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
117981
1.10 KIPS |
|
|
Style Transfer (SP)
|
100% |
1062
1.36 IPS |
|
|
Style Transfer (HP)
|
98% |
85515
110.3 IPS |
|
|
Style Transfer (Q)
|
98% |
422982
545.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
355
13.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
45990
1.70 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103635
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
451
601.6 IPS |
|
|
Text Classification (HP)
|
100% |
3108
4.15 KIPS |
|
|
Text Classification (Q)
|
93% |
6887
9.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
716
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
3824
65.9 IPS |
|
|
Machine Translation (Q)
|
55% |
2614
68.5 IPS |
