alps k6989v1_64_pre
Geekbench ML Score
3231
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 04:49 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
976
182.6 IPS |
|
|
Image Classification (F16)
|
100% |
4036
755.3 IPS |
|
|
Image Classification (I8)
|
97% |
7479
1.40 KIPS |
|
|
Image Segmentation (F32)
|
100% |
650
10.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3946
65.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1788
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8659
10.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
17837
21.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
71511
86.6 IPS |
|
|
Object Detection (F32)
|
100% |
683
51.0 IPS |
|
|
Object Detection (F16)
|
100% |
2887
215.5 IPS |
|
|
Object Detection (I8)
|
64% |
3230
241.1 IPS |
|
|
Face Detection (F32)
|
100% |
3489
41.5 IPS |
|
|
Face Detection (F16)
|
97% |
12197
145.0 IPS |
|
|
Face Detection (I8)
|
86% |
11286
134.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
929
7.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
18942
146.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
38676
299.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2552
3.36 IPS |
|
|
Style Transfer (F16)
|
100% |
2403
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4690
6.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2822
100.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7405
264.4 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
16320
582.8 IPS |
|
|
Text Classification (F32)
|
100% |
87
125.1 IPS |
|
|
Text Classification (F16)
|
100% |
1490
2.14 KIPS |
|
|
Text Classification (I8)
|
76% |
1500
2.16 KIPS |
|
|
Machine Translation (F32)
|
100% |
329
6.06 IPS |
|
|
Machine Translation (F16)
|
100% |
1861
34.2 IPS |
|
|
Machine Translation (I8)
|
76% |
526
9.69 IPS |
