alps aiv8195p1_64_bsp
Geekbench ML Score
297
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 03:55 AM |
| Views | 5 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.9 IPS |
|
|
Image Classification (F16)
|
100% |
301
56.3 IPS |
|
|
Image Classification (I8)
|
97% |
257
48.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
209
3.49 IPS |
|
|
Image Segmentation (F16)
|
100% |
334
5.58 IPS |
|
|
Image Segmentation (I8)
|
98% |
326
5.44 IPS |
|
|
Pose Estimation (F32)
|
100% |
182
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
216
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
216
0.26 IPS |
|
|
Object Detection (F32)
|
100% |
97
7.25 IPS |
|
|
Object Detection (F16)
|
100% |
143
10.7 IPS |
|
|
Object Detection (I8)
|
62% |
117
8.71 IPS |
|
|
Face Detection (F32)
|
100% |
460
5.47 IPS |
|
|
Face Detection (F16)
|
98% |
560
6.66 IPS |
|
|
Face Detection (I8)
|
86% |
520
6.18 IPS |
|
|
Depth Estimation (F32)
|
100% |
340
2.64 IPS |
|
|
Depth Estimation (F16)
|
100% |
435
3.37 IPS |
|
|
Depth Estimation (I8)
|
95% |
447
3.47 IPS |
|
|
Style Transfer (F32)
|
100% |
705
0.93 IPS |
|
|
Style Transfer (F16)
|
100% |
987
1.30 IPS |
|
|
Style Transfer (I8)
|
98% |
984
1.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
178
6.37 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
258
9.22 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
246
8.78 IPS |
|
|
Text Classification (F32)
|
100% |
185
265.8 IPS |
|
|
Text Classification (F16)
|
100% |
185
265.9 IPS |
|
|
Text Classification (I8)
|
92% |
351
504.2 IPS |
|
|
Machine Translation (F32)
|
100% |
352
6.49 IPS |
|
|
Machine Translation (F16)
|
100% |
352
6.47 IPS |
|
|
Machine Translation (I8)
|
64% |
346
6.37 IPS |
