Samsung Galaxy M31
Geekbench ML Score
164
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 04:33 AM |
| Views | 2 |
System Information
| 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 |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
95
17.7 IPS |
|
|
Image Classification (F16)
|
100% |
112
21.0 IPS |
|
|
Image Classification (I8)
|
97% |
57
10.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
122
2.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
124
2.06 IPS |
|
|
Image Segmentation (I8)
|
98% |
149
2.49 IPS |
|
|
Pose Estimation (F32)
|
100% |
219
0.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
215
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
570
0.69 IPS |
|
|
Object Detection (F32)
|
100% |
114
8.54 IPS |
|
|
Object Detection (F16)
|
100% |
77
5.78 IPS |
|
|
Object Detection (I8)
|
61% |
79
5.91 IPS |
|
|
Face Detection (F32)
|
100% |
178
2.12 IPS |
|
|
Face Detection (F16)
|
100% |
179
2.13 IPS |
|
|
Face Detection (I8)
|
86% |
234
2.78 IPS |
|
|
Depth Estimation (F32)
|
100% |
231
1.79 IPS |
|
|
Depth Estimation (F16)
|
100% |
230
1.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
391
3.03 IPS |
|
|
Style Transfer (F32)
|
100% |
410
0.54 IPS |
|
|
Style Transfer (F16)
|
100% |
412
0.54 IPS |
|
|
Style Transfer (I8)
|
98% |
844
1.11 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
144
5.14 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
163
5.83 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
175
6.26 IPS |
|
|
Text Classification (F32)
|
100% |
158
227.1 IPS |
|
|
Text Classification (F16)
|
100% |
157
225.7 IPS |
|
|
Text Classification (I8)
|
92% |
126
181.3 IPS |
|
|
Machine Translation (F32)
|
100% |
60
1.11 IPS |
|
|
Machine Translation (F16)
|
100% |
53
0.97 IPS |
|
|
Machine Translation (I8)
|
64% |
140
2.58 IPS |
