incar M10_R02
Geekbench AI Score
134
Single Precision Score
131
Half Precision Score
158
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 12 2024 10:30 AM |
| Views | 10 |
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% |
62
11.6 IPS |
|
|
Image Classification (HP)
|
100% |
65
12.1 IPS |
|
|
Image Classification (Q)
|
100% |
107
19.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
90
1.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
84
1.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
152
2.48 IPS |
|
|
Pose Estimation (SP)
|
100% |
318
0.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
309
0.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
241
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
68
5.43 IPS |
|
|
Object Detection (HP)
|
100% |
69
5.47 IPS |
|
|
Object Detection (Q)
|
83% |
104
8.40 IPS |
|
|
Face Detection (SP)
|
100% |
156
1.85 IPS |
|
|
Face Detection (HP)
|
100% |
156
1.86 IPS |
|
|
Face Detection (Q)
|
95% |
273
3.26 IPS |
|
|
Depth Estimation (SP)
|
100% |
214
1.65 IPS |
|
|
Depth Estimation (HP)
|
99% |
196
1.51 IPS |
|
|
Depth Estimation (Q)
|
64% |
235
2.15 IPS |
|
|
Style Transfer (SP)
|
89% |
579
0.75 IPS |
|
|
Style Transfer (HP)
|
89% |
584
0.76 IPS |
|
|
Style Transfer (Q)
|
98% |
589
0.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
110
4.05 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
107
3.93 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
140
5.18 IPS |
|
|
Text Classification (SP)
|
100% |
68
90.5 IPS |
|
|
Text Classification (HP)
|
100% |
66
88.5 IPS |
|
|
Text Classification (Q)
|
88% |
83
112.6 IPS |
|
|
Machine Translation (SP)
|
100% |
107
1.84 IPS |
|
|
Machine Translation (HP)
|
100% |
107
1.85 IPS |
|
|
Machine Translation (Q)
|
50% |
56
2.00 IPS |
