Anbernic RG405M
Geekbench AI Score
68
Single Precision Score
69
Half Precision Score
102
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | MidniteMarv |
| Upload Date | August 31 2025 08:40 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM Unisoc |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Anbernic RG405M |
| Model ID | Anbernic RG405M |
| Motherboard | ums512_1h10 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Unisoc |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
41
7.62 IPS |
|
|
Image Classification (HP)
|
100% |
41
7.65 IPS |
|
|
Image Classification (Q)
|
97% |
266
49.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
58
0.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
57
0.92 IPS |
|
|
Image Segmentation (Q)
|
73% |
186
3.22 IPS |
|
|
Pose Estimation (SP)
|
100% |
79
0.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
79
0.09 IPS |
|
|
Pose Estimation (Q)
|
0
|
||
|
Object Detection (SP)
|
100% |
42
3.31 IPS |
|
|
Object Detection (HP)
|
100% |
42
3.32 IPS |
|
|
Object Detection (Q)
|
84% |
236
19.0 IPS |
|
|
Face Detection (SP)
|
100% |
87
1.04 IPS |
|
|
Face Detection (HP)
|
100% |
88
1.05 IPS |
|
|
Face Detection (Q)
|
97% |
496
5.91 IPS |
|
|
Depth Estimation (SP)
|
100% |
86
0.66 IPS |
|
|
Depth Estimation (HP)
|
99% |
90
0.69 IPS |
|
|
Depth Estimation (Q)
|
64% |
232
2.12 IPS |
|
|
Style Transfer (SP)
|
100% |
148
0.19 IPS |
|
|
Style Transfer (HP)
|
100% |
148
0.19 IPS |
|
|
Style Transfer (Q)
|
98% |
522
0.67 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
47
1.73 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
47
1.73 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
617
22.9 IPS |
|
|
Text Classification (SP)
|
100% |
62
82.2 IPS |
|
|
Text Classification (HP)
|
100% |
62
82.2 IPS |
|
|
Text Classification (Q)
|
91% |
9
12.2 IPS |
|
|
Machine Translation (SP)
|
100% |
87
1.50 IPS |
|
|
Machine Translation (HP)
|
100% |
94
1.61 IPS |
|
|
Machine Translation (Q)
|
58% |
34
0.80 IPS |
