FORVIA x9 for arm64
Geekbench ML Score
105
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 08:32 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | FORVIA x9 for arm64 |
| Model ID | FORVIA x9 for arm64 |
| Motherboard | ess_plus |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3333 revision 0 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 8 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 3.17 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
56
10.4 IPS |
|
|
Image Classification (F16)
|
100% |
85
15.9 IPS |
|
|
Image Classification (I8)
|
96% |
81
15.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
74
1.24 IPS |
|
|
Image Segmentation (F16)
|
100% |
102
1.70 IPS |
|
|
Image Segmentation (I8)
|
98% |
100
1.67 IPS |
|
|
Pose Estimation (F32)
|
100% |
71
0.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
101
0.12 IPS |
|
|
Pose Estimation (I8)
|
100% |
97
0.12 IPS |
|
|
Object Detection (F32)
|
100% |
42
3.10 IPS |
|
|
Object Detection (F16)
|
100% |
60
4.50 IPS |
|
|
Object Detection (I8)
|
60% |
59
4.41 IPS |
|
|
Face Detection (F32)
|
100% |
172
2.04 IPS |
|
|
Face Detection (F16)
|
97% |
245
2.91 IPS |
|
|
Face Detection (I8)
|
86% |
224
2.67 IPS |
|
|
Depth Estimation (F32)
|
100% |
117
0.91 IPS |
|
|
Depth Estimation (F16)
|
100% |
171
1.32 IPS |
|
|
Depth Estimation (I8)
|
95% |
163
1.26 IPS |
|
|
Style Transfer (F32)
|
100% |
237
0.31 IPS |
|
|
Style Transfer (F16)
|
100% |
337
0.44 IPS |
|
|
Style Transfer (I8)
|
98% |
326
0.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
55
1.96 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
82
2.93 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
77
2.73 IPS |
|
|
Text Classification (F32)
|
100% |
58
83.7 IPS |
|
|
Text Classification (F16)
|
100% |
58
84.0 IPS |
|
|
Text Classification (I8)
|
92% |
110
158.0 IPS |
|
|
Machine Translation (F32)
|
100% |
108
1.98 IPS |
|
|
Machine Translation (F16)
|
100% |
107
1.96 IPS |
|
|
Machine Translation (I8)
|
64% |
122
2.24 IPS |
