Google nissa
Geekbench ML Score
396
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:21 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% |
245
45.9 IPS |
|
|
Image Classification (F16)
|
100% |
369
69.0 IPS |
|
|
Image Classification (I8)
|
97% |
352
65.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
291
4.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
486
8.12 IPS |
|
|
Image Segmentation (I8)
|
98% |
399
6.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
720
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
716
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
192
14.4 IPS |
|
|
Object Detection (F16)
|
100% |
269
20.1 IPS |
|
|
Object Detection (I8)
|
65% |
271
20.3 IPS |
|
|
Face Detection (F32)
|
100% |
659
7.84 IPS |
|
|
Face Detection (F16)
|
98% |
1080
12.8 IPS |
|
|
Face Detection (I8)
|
85% |
931
11.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
540
4.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
946
7.34 IPS |
|
|
Depth Estimation (I8)
|
94% |
936
7.26 IPS |
|
|
Style Transfer (F32)
|
100% |
1253
1.65 IPS |
|
|
Style Transfer (F16)
|
100% |
2241
2.95 IPS |
|
|
Style Transfer (I8)
|
98% |
2179
2.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
269
9.62 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
479
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
450
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
103
148.0 IPS |
|
|
Text Classification (F16)
|
100% |
103
147.9 IPS |
|
|
Text Classification (I8)
|
92% |
43
62.4 IPS |
|
|
Machine Translation (F32)
|
100% |
211
3.89 IPS |
|
|
Machine Translation (F16)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (I8)
|
64% |
76
1.41 IPS |
