Samsung Galaxy M31
Geekbench AI Score
61
Single Precision Score
60
Half Precision Score
92
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | harsidh |
| Upload Date | July 06 2025 10:27 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Samsung Exynos 9611 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Samsung Galaxy M31 |
| Model ID | samsung SM-M315F |
| Motherboard | exynos9611 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.74 GHz |
| Cluster 1 | 4 Cores @ 1.74 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 5.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
33
6.20 IPS |
|
|
Image Classification (HP)
|
100% |
34
6.24 IPS |
|
|
Image Classification (Q)
|
99% |
57
10.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
45
0.73 IPS |
|
|
Image Segmentation (HP)
|
100% |
45
0.74 IPS |
|
|
Image Segmentation (Q)
|
98% |
63
1.03 IPS |
|
|
Pose Estimation (SP)
|
100% |
65
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
65
0.08 IPS |
|
|
Pose Estimation (Q)
|
98% |
123
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
34
2.68 IPS |
|
|
Object Detection (HP)
|
100% |
34
2.68 IPS |
|
|
Object Detection (Q)
|
87% |
59
4.76 IPS |
|
|
Face Detection (SP)
|
100% |
88
1.05 IPS |
|
|
Face Detection (HP)
|
100% |
89
1.06 IPS |
|
|
Face Detection (Q)
|
97% |
136
1.63 IPS |
|
|
Depth Estimation (SP)
|
100% |
80
0.61 IPS |
|
|
Depth Estimation (HP)
|
99% |
80
0.61 IPS |
|
|
Depth Estimation (Q)
|
64% |
117
1.06 IPS |
|
|
Style Transfer (SP)
|
100% |
149
0.19 IPS |
|
|
Style Transfer (HP)
|
100% |
149
0.19 IPS |
|
|
Style Transfer (Q)
|
98% |
374
0.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
53
1.96 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
45
1.68 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
73
2.70 IPS |
|
|
Text Classification (SP)
|
100% |
48
64.5 IPS |
|
|
Text Classification (HP)
|
100% |
48
64.3 IPS |
|
|
Text Classification (Q)
|
91% |
63
84.2 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.47 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.49 IPS |
|
|
Machine Translation (Q)
|
57% |
64
1.56 IPS |
