alps aiv8195p1_64_bsp
Geekbench ML Score
816
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 02:46 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | alps aiv8195p1_64_bsp |
| Model ID | alps aiv8195p1_64_bsp |
| Motherboard | aiv8195p1_64_bsp |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 6.98 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
287
53.8 IPS |
|
|
Image Classification (F16)
|
100% |
1519
284.2 IPS |
|
|
Image Classification (I8)
|
97% |
2254
421.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
455
7.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
714
11.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1545
25.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1695
2.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
4587
5.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
11521
14.0 IPS |
|
|
Object Detection (F32)
|
100% |
275
20.5 IPS |
|
|
Object Detection (F16)
|
100% |
1299
97.0 IPS |
|
|
Object Detection (I8)
|
0
|
||
|
Face Detection (F32)
|
25% |
404
4.81 IPS |
|
|
Face Detection (F16)
|
97% |
3799
45.2 IPS |
|
|
Face Detection (I8)
|
86% |
5040
59.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
555
4.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
709
5.50 IPS |
|
|
Depth Estimation (I8)
|
95% |
1831
14.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1135
1.49 IPS |
|
|
Style Transfer (F16)
|
100% |
3038
4.00 IPS |
|
|
Style Transfer (I8)
|
98% |
3498
4.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
735
26.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3454
123.4 IPS |
|
|
Image Super-Resolution (I8)
|
64% |
6193
221.2 IPS |
|
|
Text Classification (F32)
|
100% |
103
147.7 IPS |
|
|
Text Classification (F16)
|
100% |
160
229.8 IPS |
|
|
Text Classification (I8)
|
92% |
307
441.7 IPS |
|
|
Machine Translation (F32)
|
100% |
263
4.84 IPS |
|
|
Machine Translation (F16)
|
100% |
330
6.07 IPS |
|
|
Machine Translation (I8)
|
57% |
307
5.66 IPS |
