Samsung Galaxy S25 Ultra
Geekbench AI Score
2317
Single Precision Score
3294
Half Precision Score
2879
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | abhimanbhau |
| Upload Date | January 09 2026 04:05 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938U1 |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1772
329.5 IPS |
|
|
Image Classification (HP)
|
100% |
2772
515.5 IPS |
|
|
Image Classification (Q)
|
100% |
2795
519.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3186
51.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5493
89.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5393
87.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
13922
16.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
24808
28.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
24144
28.3 IPS |
|
|
Object Detection (SP)
|
100% |
1532
121.5 IPS |
|
|
Object Detection (HP)
|
99% |
1029
81.6 IPS |
|
|
Object Detection (Q)
|
85% |
988
79.5 IPS |
|
|
Face Detection (SP)
|
100% |
3382
40.2 IPS |
|
|
Face Detection (HP)
|
100% |
5007
59.5 IPS |
|
|
Face Detection (Q)
|
97% |
5142
61.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4655
35.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
6753
52.2 IPS |
|
|
Depth Estimation (Q)
|
61% |
5312
51.8 IPS |
|
|
Style Transfer (SP)
|
100% |
12941
16.6 IPS |
|
|
Style Transfer (HP)
|
100% |
28149
36.2 IPS |
|
|
Style Transfer (Q)
|
98% |
27864
35.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2840
104.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4298
158.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4290
159.0 IPS |
|
|
Text Classification (SP)
|
35% |
67
648.5 IPS |
|
|
Text Classification (HP)
|
35% |
66
603.9 IPS |
|
|
Text Classification (Q)
|
33% |
53
597.1 IPS |
|
|
Machine Translation (SP)
|
100% |
958
16.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1436
24.7 IPS |
|
|
Machine Translation (Q)
|
48% |
629
24.1 IPS |
