incar M10_R02
Geekbench AI Score
124
Single Precision Score
130
Half Precision Score
157
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 12 2024 03:50 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | incar M10_R02 |
| Model ID | incar M10_R02 |
| Motherboard | rk30sdk |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 2.87 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
61
11.3 IPS |
|
|
Image Classification (HP)
|
100% |
64
11.9 IPS |
|
|
Image Classification (Q)
|
100% |
104
19.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
86
1.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
89
1.44 IPS |
|
|
Image Segmentation (Q)
|
98% |
153
2.48 IPS |
|
|
Pose Estimation (SP)
|
100% |
297
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
304
0.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
235
0.28 IPS |
|
|
Object Detection (SP)
|
100% |
67
5.30 IPS |
|
|
Object Detection (HP)
|
100% |
67
5.34 IPS |
|
|
Object Detection (Q)
|
83% |
105
8.47 IPS |
|
|
Face Detection (SP)
|
100% |
151
1.79 IPS |
|
|
Face Detection (HP)
|
100% |
160
1.90 IPS |
|
|
Face Detection (Q)
|
95% |
268
3.20 IPS |
|
|
Depth Estimation (SP)
|
100% |
139
1.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
191
1.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
219
2.01 IPS |
|
|
Style Transfer (SP)
|
89% |
561
0.73 IPS |
|
|
Style Transfer (HP)
|
89% |
560
0.73 IPS |
|
|
Style Transfer (Q)
|
98% |
577
0.74 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
110
4.05 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
107
3.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
139
5.14 IPS |
|
|
Text Classification (SP)
|
100% |
66
88.4 IPS |
|
|
Text Classification (HP)
|
100% |
66
87.6 IPS |
|
|
Text Classification (Q)
|
88% |
90
121.9 IPS |
|
|
Machine Translation (SP)
|
100% |
101
1.75 IPS |
|
|
Machine Translation (HP)
|
100% |
103
1.78 IPS |
|
|
Machine Translation (Q)
|
50% |
58
2.06 IPS |
