alps k6989v1_64_pre
Geekbench ML Score
1136
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 05:03 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps k6989v1_64_pre |
| Model ID | alps k6989v1_64_pre |
| Motherboard | k6989v1_64_pre |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 10.97 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
683
127.8 IPS |
|
|
Image Classification (F16)
|
100% |
718
134.4 IPS |
|
|
Image Classification (I8)
|
97% |
890
166.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
906
15.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
939
15.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
997
16.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1177
1.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
1061
1.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
4676
5.66 IPS |
|
|
Object Detection (F32)
|
100% |
667
49.8 IPS |
|
|
Object Detection (F16)
|
100% |
649
48.5 IPS |
|
|
Object Detection (I8)
|
61% |
809
60.4 IPS |
|
|
Face Detection (F32)
|
100% |
1558
18.5 IPS |
|
|
Face Detection (F16)
|
100% |
1459
17.3 IPS |
|
|
Face Detection (I8)
|
86% |
2032
24.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1222
9.48 IPS |
|
|
Depth Estimation (F16)
|
100% |
1236
9.59 IPS |
|
|
Depth Estimation (I8)
|
95% |
1857
14.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1876
2.47 IPS |
|
|
Style Transfer (F16)
|
100% |
1937
2.55 IPS |
|
|
Style Transfer (I8)
|
98% |
4206
5.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
774
27.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
759
27.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2311
82.5 IPS |
|
|
Text Classification (F32)
|
100% |
752
1.08 KIPS |
|
|
Text Classification (F16)
|
100% |
765
1.10 KIPS |
|
|
Text Classification (I8)
|
92% |
517
743.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1378
25.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1315
24.2 IPS |
|
|
Machine Translation (I8)
|
64% |
425
7.82 IPS |
