Samsung Galaxy S26+ samsung SM-S947B
Geekbench AI Score
3925
Single Precision Score
44743
Half Precision Score
85114
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | February 27 2026 12:50 PM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S947B |
| Model ID | samsung SM-S947B |
| Motherboard | s5e9965 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3468 revision 0 |
| Base Frequency | 2.76 GHz |
| Cluster 1 | 6 Cores @ 2.76 GHz |
| Cluster 2 | 3 Cores @ 3.26 GHz |
| Cluster 3 | 1 Core @ 3.80 GHz |
| Memory Information | |
|---|---|
| Size | 11.36 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1823
339.0 IPS |
|
|
Image Classification (HP)
|
100% |
23916
4.45 KIPS |
|
|
Image Classification (Q)
|
100% |
49576
9.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3591
58.2 IPS |
|
|
Image Segmentation (HP)
|
97% |
25118
408.6 IPS |
|
|
Image Segmentation (Q)
|
96% |
77313
1.26 KIPS |
|
|
Pose Estimation (SP)
|
100% |
18132
21.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
144069
168.1 IPS |
|
|
Pose Estimation (Q)
|
97% |
570521
668.1 IPS |
|
|
Object Detection (SP)
|
100% |
1956
155.1 IPS |
|
|
Object Detection (HP)
|
100% |
24280
1.93 KIPS |
|
|
Object Detection (Q)
|
88% |
36078
2.89 KIPS |
|
|
Face Detection (SP)
|
100% |
6066
72.1 IPS |
|
|
Face Detection (HP)
|
100% |
62078
737.6 IPS |
|
|
Face Detection (Q)
|
94% |
162587
1.94 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8191
63.1 IPS |
|
|
Depth Estimation (HP)
|
79% |
105965
841.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
208520
1.94 KIPS |
|
|
Style Transfer (SP)
|
100% |
35330
45.4 IPS |
|
|
Style Transfer (HP)
|
99% |
309710
398.1 IPS |
|
|
Style Transfer (Q)
|
98% |
867320
1.12 KIPS |
|
|
Image Super-Resolution (SP)
|
100% |
4125
152.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
71145
2.63 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
93505
3.46 KIPS |
|
|
Text Classification (SP)
|
100% |
558
745.1 IPS |
|
|
Text Classification (HP)
|
100% |
9649
12.9 KIPS |
|
|
Text Classification (Q)
|
93% |
9609
12.9 KIPS |
|
|
Machine Translation (SP)
|
100% |
926
16.0 IPS |
|
|
Machine Translation (HP)
|
100% |
10943
188.5 IPS |
|
|
Machine Translation (Q)
|
57% |
9574
235.9 IPS |
