DTEN Bar_DCR200
Geekbench ML Score
117
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 07:39 AM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | DTEN Bar_DCR200 |
| Model ID | DTEN Bar_DCR200 |
| Motherboard | R1-003 |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.35 GHz |
| Memory Information | |
|---|---|
| Size | 15.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
43
7.96 IPS |
|
|
Image Classification (F16)
|
100% |
43
7.97 IPS |
|
|
Image Classification (I8)
|
97% |
46
8.62 IPS |
|
|
Image Segmentation (F32)
|
100% |
173
2.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
171
2.86 IPS |
|
|
Image Segmentation (I8)
|
98% |
197
3.29 IPS |
|
|
Pose Estimation (F32)
|
100% |
484
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
475
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
1425
1.73 IPS |
|
|
Object Detection (F32)
|
100% |
66
4.92 IPS |
|
|
Object Detection (F16)
|
100% |
66
4.94 IPS |
|
|
Object Detection (I8)
|
61% |
77
5.76 IPS |
|
|
Face Detection (F32)
|
100% |
216
2.57 IPS |
|
|
Face Detection (F16)
|
100% |
219
2.61 IPS |
|
|
Face Detection (I8)
|
86% |
261
3.11 IPS |
|
|
Depth Estimation (F32)
|
100% |
206
1.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
209
1.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
273
2.12 IPS |
|
|
Style Transfer (F32)
|
100% |
780
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
792
1.04 IPS |
|
|
Style Transfer (I8)
|
98% |
2095
2.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
117
4.19 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
123
4.38 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
169
6.03 IPS |
|
|
Text Classification (F32)
|
100% |
8
11.3 IPS |
|
|
Text Classification (F16)
|
100% |
8
11.2 IPS |
|
|
Text Classification (I8)
|
92% |
9
12.5 IPS |
|
|
Machine Translation (F32)
|
100% |
21
0.39 IPS |
|
|
Machine Translation (F16)
|
100% |
21
0.39 IPS |
|
|
Machine Translation (I8)
|
64% |
22
0.40 IPS |
