Google nissa
Geekbench ML Score
404
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% |
248
46.3 IPS |
|
|
Image Classification (F16)
|
100% |
369
69.1 IPS |
|
|
Image Classification (I8)
|
97% |
352
65.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
299
5.00 IPS |
|
|
Image Segmentation (F16)
|
100% |
504
8.42 IPS |
|
|
Image Segmentation (I8)
|
98% |
400
6.67 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
720
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
713
0.86 IPS |
|
|
Object Detection (F32)
|
100% |
193
14.4 IPS |
|
|
Object Detection (F16)
|
100% |
276
20.6 IPS |
|
|
Object Detection (I8)
|
65% |
266
19.8 IPS |
|
|
Face Detection (F32)
|
100% |
693
8.24 IPS |
|
|
Face Detection (F16)
|
98% |
1085
12.9 IPS |
|
|
Face Detection (I8)
|
85% |
947
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
534
4.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
947
7.34 IPS |
|
|
Depth Estimation (I8)
|
94% |
939
7.28 IPS |
|
|
Style Transfer (F32)
|
100% |
1248
1.64 IPS |
|
|
Style Transfer (F16)
|
100% |
2239
2.94 IPS |
|
|
Style Transfer (I8)
|
98% |
2193
2.89 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
265
9.46 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
479
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
449
16.0 IPS |
|
|
Text Classification (F32)
|
100% |
113
162.8 IPS |
|
|
Text Classification (F16)
|
100% |
113
163.1 IPS |
|
|
Text Classification (I8)
|
92% |
44
63.5 IPS |
|
|
Machine Translation (F32)
|
100% |
236
4.34 IPS |
|
|
Machine Translation (F16)
|
100% |
237
4.35 IPS |
|
|
Machine Translation (I8)
|
64% |
78
1.44 IPS |
