alps k6989v1_64_pre
Geekbench ML Score
1086
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 09:34 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% |
650
121.7 IPS |
|
|
Image Classification (F16)
|
100% |
670
125.4 IPS |
|
|
Image Classification (I8)
|
97% |
865
161.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
854
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
865
14.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1032
17.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1068
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
1043
1.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
4608
5.58 IPS |
|
|
Object Detection (F32)
|
100% |
577
43.1 IPS |
|
|
Object Detection (F16)
|
100% |
594
44.3 IPS |
|
|
Object Detection (I8)
|
61% |
800
59.7 IPS |
|
|
Face Detection (F32)
|
100% |
1454
17.3 IPS |
|
|
Face Detection (F16)
|
100% |
1413
16.8 IPS |
|
|
Face Detection (I8)
|
86% |
2044
24.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1195
9.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
1158
8.98 IPS |
|
|
Depth Estimation (I8)
|
95% |
1893
14.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1835
2.41 IPS |
|
|
Style Transfer (F16)
|
100% |
1671
2.20 IPS |
|
|
Style Transfer (I8)
|
98% |
4265
5.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
762
27.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2133
76.2 IPS |
|
|
Text Classification (F32)
|
100% |
706
1.01 KIPS |
|
|
Text Classification (F16)
|
100% |
689
989.7 IPS |
|
|
Text Classification (I8)
|
92% |
502
721.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1305
24.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1225
22.5 IPS |
|
|
Machine Translation (I8)
|
64% |
423
7.78 IPS |
