alps k6989v1_64_pre
Geekbench ML Score
1133
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 02:58 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% |
680
127.3 IPS |
|
|
Image Classification (F16)
|
100% |
726
135.9 IPS |
|
|
Image Classification (I8)
|
97% |
899
168.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
933
15.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
927
15.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1023
17.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1160
1.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
1029
1.25 IPS |
|
|
Pose Estimation (I8)
|
100% |
4676
5.66 IPS |
|
|
Object Detection (F32)
|
100% |
631
47.1 IPS |
|
|
Object Detection (F16)
|
100% |
637
47.5 IPS |
|
|
Object Detection (I8)
|
61% |
839
62.6 IPS |
|
|
Face Detection (F32)
|
100% |
1559
18.5 IPS |
|
|
Face Detection (F16)
|
100% |
1457
17.3 IPS |
|
|
Face Detection (I8)
|
86% |
1972
23.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1227
9.52 IPS |
|
|
Depth Estimation (F16)
|
100% |
1237
9.59 IPS |
|
|
Depth Estimation (I8)
|
95% |
1828
14.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1895
2.49 IPS |
|
|
Style Transfer (F16)
|
100% |
1899
2.50 IPS |
|
|
Style Transfer (I8)
|
98% |
4226
5.56 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
766
27.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2197
78.5 IPS |
|
|
Text Classification (F32)
|
100% |
757
1.09 KIPS |
|
|
Text Classification (F16)
|
100% |
763
1.10 KIPS |
|
|
Text Classification (I8)
|
92% |
533
765.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1380
25.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1316
24.2 IPS |
|
|
Machine Translation (I8)
|
64% |
430
7.91 IPS |
