Samsung Galaxy S25 Ultra
Geekbench AI Score
669
Single Precision Score
27538
Half Precision Score
61711
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 07 2025 11:27 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S25 Ultra |
| Model ID | samsung SM-S938Q |
| 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% |
459
85.4 IPS |
|
|
Image Classification (HP)
|
100% |
21400
3.98 KIPS |
|
|
Image Classification (Q)
|
97% |
49167
9.18 KIPS |
|
|
Image Segmentation (SP)
|
100% |
584
9.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
13573
220.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
42346
688.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
765
0.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
123917
144.6 IPS |
|
|
Pose Estimation (Q)
|
98% |
478283
559.8 IPS |
|
|
Object Detection (SP)
|
100% |
366
29.0 IPS |
|
|
Object Detection (HP)
|
100% |
19431
1.54 KIPS |
|
|
Object Detection (Q)
|
85% |
22596
1.82 KIPS |
|
|
Face Detection (SP)
|
100% |
952
11.3 IPS |
|
|
Face Detection (HP)
|
100% |
42818
508.8 IPS |
|
|
Face Detection (Q)
|
97% |
147422
1.76 KIPS |
|
|
Depth Estimation (SP)
|
100% |
869
6.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
84502
651.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
146182
1.35 KIPS |
|
|
Style Transfer (SP)
|
100% |
1436
1.85 IPS |
|
|
Style Transfer (HP)
|
98% |
98919
127.6 IPS |
|
|
Style Transfer (Q)
|
98% |
492410
635.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
424
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54399
2.01 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134511
4.98 KIPS |
|
|
Text Classification (SP)
|
100% |
531
708.7 IPS |
|
|
Text Classification (HP)
|
100% |
3896
5.20 KIPS |
|
|
Text Classification (Q)
|
93% |
7940
10.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
898
15.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4728
81.4 IPS |
|
|
Machine Translation (Q)
|
56% |
3141
80.9 IPS |
