alps k6989v1_64_pre
Geekbench ML Score
1131
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 03:03 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% |
673
126.0 IPS |
|
|
Image Classification (F16)
|
100% |
712
133.2 IPS |
|
|
Image Classification (I8)
|
97% |
903
168.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
927
15.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
943
15.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
984
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1149
1.39 IPS |
|
|
Pose Estimation (F16)
|
100% |
1096
1.33 IPS |
|
|
Pose Estimation (I8)
|
100% |
4635
5.61 IPS |
|
|
Object Detection (F32)
|
100% |
614
45.9 IPS |
|
|
Object Detection (F16)
|
100% |
606
45.2 IPS |
|
|
Object Detection (I8)
|
61% |
822
61.4 IPS |
|
|
Face Detection (F32)
|
100% |
1485
17.7 IPS |
|
|
Face Detection (F16)
|
100% |
1523
18.1 IPS |
|
|
Face Detection (I8)
|
86% |
2076
24.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1256
9.74 IPS |
|
|
Depth Estimation (F16)
|
100% |
1245
9.66 IPS |
|
|
Depth Estimation (I8)
|
95% |
1982
15.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1923
2.53 IPS |
|
|
Style Transfer (F16)
|
100% |
1903
2.50 IPS |
|
|
Style Transfer (I8)
|
98% |
4440
5.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
784
28.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2142
76.5 IPS |
|
|
Text Classification (F32)
|
100% |
732
1.05 KIPS |
|
|
Text Classification (F16)
|
100% |
739
1.06 KIPS |
|
|
Text Classification (I8)
|
92% |
503
723.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1331
24.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1282
23.6 IPS |
|
|
Machine Translation (I8)
|
64% |
436
8.02 IPS |
