Google nissa
Geekbench ML Score
400
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:13 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google nissa |
| Model ID | Google nissa |
| Motherboard | joxer |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 6.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
249
46.6 IPS |
|
|
Image Classification (F16)
|
100% |
385
72.1 IPS |
|
|
Image Classification (I8)
|
97% |
372
69.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
298
4.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
496
8.29 IPS |
|
|
Image Segmentation (I8)
|
98% |
393
6.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
381
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
718
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
718
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
215
16.1 IPS |
|
|
Object Detection (F16)
|
100% |
275
20.5 IPS |
|
|
Object Detection (I8)
|
65% |
264
19.7 IPS |
|
|
Face Detection (F32)
|
100% |
656
7.80 IPS |
|
|
Face Detection (F16)
|
98% |
1081
12.9 IPS |
|
|
Face Detection (I8)
|
85% |
946
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
537
4.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
949
7.36 IPS |
|
|
Depth Estimation (I8)
|
94% |
936
7.26 IPS |
|
|
Style Transfer (F32)
|
100% |
1254
1.65 IPS |
|
|
Style Transfer (F16)
|
100% |
2237
2.94 IPS |
|
|
Style Transfer (I8)
|
98% |
2186
2.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
269
9.59 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
477
17.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
448
16.0 IPS |
|
|
Text Classification (F32)
|
100% |
103
147.7 IPS |
|
|
Text Classification (F16)
|
100% |
103
148.1 IPS |
|
|
Text Classification (I8)
|
92% |
44
62.6 IPS |
|
|
Machine Translation (F32)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (F16)
|
100% |
212
3.89 IPS |
|
|
Machine Translation (I8)
|
64% |
77
1.42 IPS |
