alps k6993v1_64_for_dx6_vdo
Geekbench ML Score
874
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 24 2025 03:20 AM |
| Views | 13 |
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% |
543
101.6 IPS |
|
|
Image Classification (F16)
|
100% |
575
107.6 IPS |
|
|
Image Classification (I8)
|
97% |
602
112.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
751
12.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
752
12.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
999
16.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
846
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
839
1.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
3703
4.48 IPS |
|
|
Object Detection (F32)
|
100% |
530
39.6 IPS |
|
|
Object Detection (F16)
|
100% |
550
41.1 IPS |
|
|
Object Detection (I8)
|
61% |
632
47.2 IPS |
|
|
Face Detection (F32)
|
100% |
1192
14.2 IPS |
|
|
Face Detection (F16)
|
100% |
1164
13.8 IPS |
|
|
Face Detection (I8)
|
86% |
2123
25.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
994
7.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
997
7.73 IPS |
|
|
Depth Estimation (I8)
|
95% |
1598
12.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1401
1.84 IPS |
|
|
Style Transfer (F16)
|
100% |
1397
1.84 IPS |
|
|
Style Transfer (I8)
|
98% |
3088
4.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
662
23.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
633
22.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1915
68.4 IPS |
|
|
Text Classification (F32)
|
100% |
553
795.3 IPS |
|
|
Text Classification (F16)
|
100% |
515
739.9 IPS |
|
|
Text Classification (I8)
|
92% |
301
432.5 IPS |
|
|
Machine Translation (F32)
|
100% |
938
17.3 IPS |
|
|
Machine Translation (F16)
|
100% |
886
16.3 IPS |
|
|
Machine Translation (I8)
|
64% |
216
3.97 IPS |
