incar M10_R02
Geekbench AI Score
130
Single Precision Score
131
Half Precision Score
160
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 12 2024 11:18 AM |
| Views | 34 |
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% |
66
12.2 IPS |
|
|
Image Classification (HP)
|
100% |
66
12.4 IPS |
|
|
Image Classification (Q)
|
100% |
106
19.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
90
1.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
88
1.43 IPS |
|
|
Image Segmentation (Q)
|
98% |
151
2.46 IPS |
|
|
Pose Estimation (SP)
|
100% |
318
0.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
319
0.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
238
0.28 IPS |
|
|
Object Detection (SP)
|
100% |
68
5.42 IPS |
|
|
Object Detection (HP)
|
100% |
68
5.39 IPS |
|
|
Object Detection (Q)
|
83% |
107
8.65 IPS |
|
|
Face Detection (SP)
|
100% |
158
1.87 IPS |
|
|
Face Detection (HP)
|
100% |
149
1.77 IPS |
|
|
Face Detection (Q)
|
95% |
280
3.34 IPS |
|
|
Depth Estimation (SP)
|
100% |
151
1.16 IPS |
|
|
Depth Estimation (HP)
|
99% |
196
1.51 IPS |
|
|
Depth Estimation (Q)
|
64% |
240
2.20 IPS |
|
|
Style Transfer (SP)
|
89% |
571
0.74 IPS |
|
|
Style Transfer (HP)
|
89% |
581
0.75 IPS |
|
|
Style Transfer (Q)
|
98% |
583
0.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
110
4.08 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
108
3.99 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
143
5.29 IPS |
|
|
Text Classification (SP)
|
100% |
69
91.5 IPS |
|
|
Text Classification (HP)
|
100% |
61
81.3 IPS |
|
|
Text Classification (Q)
|
88% |
86
116.0 IPS |
|
|
Machine Translation (SP)
|
100% |
110
1.89 IPS |
|
|
Machine Translation (HP)
|
100% |
106
1.83 IPS |
|
|
Machine Translation (Q)
|
50% |
56
2.00 IPS |
