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 08:15 AM |
| Views | 4 |
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% |
42
7.93 IPS |
|
|
Image Classification (F16)
|
100% |
42
7.86 IPS |
|
|
Image Classification (I8)
|
97% |
46
8.66 IPS |
|
|
Image Segmentation (F32)
|
100% |
175
2.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
167
2.80 IPS |
|
|
Image Segmentation (I8)
|
98% |
189
3.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
480
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
478
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
1422
1.72 IPS |
|
|
Object Detection (F32)
|
100% |
65
4.86 IPS |
|
|
Object Detection (F16)
|
100% |
66
4.96 IPS |
|
|
Object Detection (I8)
|
61% |
75
5.58 IPS |
|
|
Face Detection (F32)
|
100% |
217
2.58 IPS |
|
|
Face Detection (F16)
|
100% |
218
2.59 IPS |
|
|
Face Detection (I8)
|
86% |
264
3.14 IPS |
|
|
Depth Estimation (F32)
|
100% |
210
1.63 IPS |
|
|
Depth Estimation (F16)
|
100% |
207
1.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
273
2.12 IPS |
|
|
Style Transfer (F32)
|
100% |
788
1.04 IPS |
|
|
Style Transfer (F16)
|
100% |
785
1.03 IPS |
|
|
Style Transfer (I8)
|
98% |
2069
2.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
119
4.24 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
119
4.26 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
168
6.00 IPS |
|
|
Text Classification (F32)
|
100% |
8
11.2 IPS |
|
|
Text Classification (F16)
|
100% |
8
11.2 IPS |
|
|
Text Classification (I8)
|
92% |
9
12.6 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 |
