DTEN Bar_DCR200
Geekbench ML Score
116
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 10:10 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
7.90 IPS |
|
|
Image Classification (F16)
|
100% |
42
7.91 IPS |
|
|
Image Classification (I8)
|
97% |
46
8.67 IPS |
|
|
Image Segmentation (F32)
|
100% |
171
2.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
171
2.86 IPS |
|
|
Image Segmentation (I8)
|
98% |
186
3.11 IPS |
|
|
Pose Estimation (F32)
|
100% |
471
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
476
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
1372
1.66 IPS |
|
|
Object Detection (F32)
|
100% |
66
4.91 IPS |
|
|
Object Detection (F16)
|
100% |
66
4.95 IPS |
|
|
Object Detection (I8)
|
61% |
76
5.65 IPS |
|
|
Face Detection (F32)
|
100% |
214
2.55 IPS |
|
|
Face Detection (F16)
|
100% |
214
2.55 IPS |
|
|
Face Detection (I8)
|
86% |
264
3.14 IPS |
|
|
Depth Estimation (F32)
|
100% |
208
1.62 IPS |
|
|
Depth Estimation (F16)
|
100% |
209
1.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
274
2.13 IPS |
|
|
Style Transfer (F32)
|
100% |
787
1.04 IPS |
|
|
Style Transfer (F16)
|
100% |
790
1.04 IPS |
|
|
Style Transfer (I8)
|
98% |
2060
2.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
119
4.27 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
119
4.25 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
166
5.91 IPS |
|
|
Text Classification (F32)
|
100% |
8
11.1 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 |
