Google nissa
Geekbench ML Score
403
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:22 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% |
261
48.8 IPS |
|
|
Image Classification (F16)
|
100% |
399
74.6 IPS |
|
|
Image Classification (I8)
|
97% |
393
73.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
299
4.99 IPS |
|
|
Image Segmentation (F16)
|
100% |
501
8.37 IPS |
|
|
Image Segmentation (I8)
|
98% |
374
6.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
722
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
718
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
192
14.4 IPS |
|
|
Object Detection (F16)
|
100% |
294
22.0 IPS |
|
|
Object Detection (I8)
|
65% |
270
20.2 IPS |
|
|
Face Detection (F32)
|
100% |
665
7.91 IPS |
|
|
Face Detection (F16)
|
98% |
1085
12.9 IPS |
|
|
Face Detection (I8)
|
85% |
941
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
947
7.34 IPS |
|
|
Depth Estimation (I8)
|
94% |
942
7.30 IPS |
|
|
Style Transfer (F32)
|
100% |
1262
1.66 IPS |
|
|
Style Transfer (F16)
|
100% |
2231
2.93 IPS |
|
|
Style Transfer (I8)
|
98% |
2199
2.89 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
269
9.62 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
479
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
458
16.4 IPS |
|
|
Text Classification (F32)
|
100% |
105
151.1 IPS |
|
|
Text Classification (F16)
|
100% |
105
151.1 IPS |
|
|
Text Classification (I8)
|
92% |
44
62.6 IPS |
|
|
Machine Translation (F32)
|
100% |
218
4.01 IPS |
|
|
Machine Translation (F16)
|
100% |
216
3.97 IPS |
|
|
Machine Translation (I8)
|
64% |
77
1.41 IPS |
