Samsung Galaxy S25 Ultra
Geekbench AI Score
2507
Single Precision Score
2463
Half Precision Score
3995
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | September 14 2025 11:55 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938B |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1973
366.9 IPS |
|
|
Image Classification (HP)
|
100% |
2075
385.8 IPS |
|
|
Image Classification (Q)
|
100% |
4393
817.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2465
40.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2336
37.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
5341
86.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5341
6.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
5127
5.98 IPS |
|
|
Pose Estimation (Q)
|
84% |
12782
15.2 IPS |
|
|
Object Detection (SP)
|
98% |
1602
127.5 IPS |
|
|
Object Detection (HP)
|
98% |
1584
126.1 IPS |
|
|
Object Detection (Q)
|
83% |
1834
148.2 IPS |
|
|
Face Detection (SP)
|
100% |
3313
39.4 IPS |
|
|
Face Detection (HP)
|
100% |
3244
38.5 IPS |
|
|
Face Detection (Q)
|
95% |
6259
74.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
3700
28.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4332
33.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
9965
91.3 IPS |
|
|
Style Transfer (SP)
|
89% |
11106
14.4 IPS |
|
|
Style Transfer (HP)
|
89% |
11343
14.7 IPS |
|
|
Style Transfer (Q)
|
98% |
25344
32.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2193
81.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1690
62.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4154
153.9 IPS |
|
|
Text Classification (SP)
|
100% |
611
815.6 IPS |
|
|
Text Classification (HP)
|
99% |
594
792.7 IPS |
|
|
Text Classification (Q)
|
88% |
544
733.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1292
22.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1305
22.5 IPS |
|
|
Machine Translation (Q)
|
50% |
528
18.7 IPS |
