alps k6989v1_64_pre
Geekbench ML Score
1119
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 05:21 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% |
678
127.0 IPS |
|
|
Image Classification (F16)
|
100% |
711
133.0 IPS |
|
|
Image Classification (I8)
|
97% |
888
166.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
916
15.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
900
15.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1013
16.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1137
1.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
1079
1.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
4635
5.61 IPS |
|
|
Object Detection (F32)
|
100% |
572
42.7 IPS |
|
|
Object Detection (F16)
|
100% |
577
43.1 IPS |
|
|
Object Detection (I8)
|
61% |
816
60.9 IPS |
|
|
Face Detection (F32)
|
100% |
1494
17.8 IPS |
|
|
Face Detection (F16)
|
100% |
1513
18.0 IPS |
|
|
Face Detection (I8)
|
86% |
2038
24.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1244
9.65 IPS |
|
|
Depth Estimation (F16)
|
100% |
1236
9.58 IPS |
|
|
Depth Estimation (I8)
|
95% |
1968
15.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1909
2.51 IPS |
|
|
Style Transfer (F16)
|
100% |
1823
2.40 IPS |
|
|
Style Transfer (I8)
|
98% |
4288
5.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
784
28.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
773
27.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2122
75.8 IPS |
|
|
Text Classification (F32)
|
100% |
736
1.06 KIPS |
|
|
Text Classification (F16)
|
100% |
745
1.07 KIPS |
|
|
Text Classification (I8)
|
92% |
519
745.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1315
24.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1259
23.2 IPS |
|
|
Machine Translation (I8)
|
64% |
426
7.84 IPS |
