Samsung Galaxy S24 Ultra
Geekbench AI Score
1062
Single Precision Score
1602
Half Precision Score
1475
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Spiike |
| Upload Date | July 16 2025 01:55 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928W |
| 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% |
662
123.1 IPS |
|
|
Image Classification (HP)
|
100% |
687
127.8 IPS |
|
|
Image Classification (Q)
|
96% |
550
102.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1218
19.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1322
21.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1061
17.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1103
1.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
2298
2.68 IPS |
|
|
Pose Estimation (Q)
|
96% |
2285
2.68 IPS |
|
|
Object Detection (SP)
|
100% |
674
53.4 IPS |
|
|
Object Detection (HP)
|
100% |
863
68.4 IPS |
|
|
Object Detection (Q)
|
87% |
813
65.3 IPS |
|
|
Face Detection (SP)
|
100% |
2083
24.7 IPS |
|
|
Face Detection (HP)
|
100% |
3761
44.7 IPS |
|
|
Face Detection (Q)
|
97% |
2803
33.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1830
14.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4002
30.9 IPS |
|
|
Depth Estimation (Q)
|
63% |
3039
28.2 IPS |
|
|
Style Transfer (SP)
|
100% |
6592
8.47 IPS |
|
|
Style Transfer (HP)
|
100% |
10824
13.9 IPS |
|
|
Style Transfer (Q)
|
98% |
9945
12.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
417
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1300
48.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1284
47.6 IPS |
|
|
Text Classification (SP)
|
100% |
429
573.2 IPS |
|
|
Text Classification (HP)
|
100% |
443
590.8 IPS |
|
|
Text Classification (Q)
|
91% |
721
968.9 IPS |
|
|
Machine Translation (SP)
|
100% |
678
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
662
11.4 IPS |
|
|
Machine Translation (Q)
|
57% |
575
14.1 IPS |
