alps k6993v1_64_for_dx6_vdo
Geekbench ML Score
470
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 21 2025 02:14 AM |
| Views | 12 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | alps k6993v1_64_for_dx6_vdo |
| Model ID | alps k6993v1_64_for_dx6_vdo |
| Motherboard | k6993v1_64_for_dx6 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3468 revision 0 |
| Base Frequency | 2.23 GHz |
| Cluster 1 | 4 Cores @ 2.23 GHz |
| Cluster 2 | 3 Cores @ 3.03 GHz |
| Cluster 3 | 1 Core @ 3.23 GHz |
| Memory Information | |
|---|---|
| Size | 10.64 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
529
99.1 IPS |
|
|
Image Classification (F16)
|
100% |
533
99.7 IPS |
|
|
Image Classification (I8)
|
97% |
566
105.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
644
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
685
11.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
596
9.95 IPS |
|
|
Pose Estimation (F32)
|
100% |
793
0.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
736
0.89 IPS |
|
|
Pose Estimation (I8)
|
100% |
3035
3.68 IPS |
|
|
Object Detection (F32)
|
100% |
440
32.8 IPS |
|
|
Object Detection (F16)
|
100% |
435
32.4 IPS |
|
|
Object Detection (I8)
|
61% |
336
25.1 IPS |
|
|
Face Detection (F32)
|
100% |
795
9.46 IPS |
|
|
Face Detection (F16)
|
100% |
665
7.90 IPS |
|
|
Face Detection (I8)
|
86% |
1118
13.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
440
3.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
375
2.91 IPS |
|
|
Depth Estimation (I8)
|
95% |
500
3.88 IPS |
|
|
Style Transfer (F32)
|
100% |
703
0.93 IPS |
|
|
Style Transfer (F16)
|
100% |
704
0.93 IPS |
|
|
Style Transfer (I8)
|
98% |
1561
2.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
216
7.70 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
225
8.04 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
632
22.6 IPS |
|
|
Text Classification (F32)
|
100% |
158
227.0 IPS |
|
|
Text Classification (F16)
|
100% |
161
231.6 IPS |
|
|
Text Classification (I8)
|
92% |
157
225.0 IPS |
|
|
Machine Translation (F32)
|
100% |
279
5.13 IPS |
|
|
Machine Translation (F16)
|
100% |
276
5.07 IPS |
|
|
Machine Translation (I8)
|
64% |
90
1.67 IPS |
