Nintendo Switch
Geekbench AI Score
52
Single Precision Score
52
Half Precision Score
87
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | TheDogDR |
| Upload Date | January 31 2025 08:39 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Nintendo Switch |
| Model ID | Nintendo Switch |
| Motherboard | |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3335 revision 1 |
| Base Frequency | 2.09 GHz |
| Cluster 1 | 4 Cores @ 2.09 GHz |
| Memory Information | |
|---|---|
| Size | 3.89 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
32
5.98 IPS |
|
|
Image Classification (HP)
|
100% |
32
5.92 IPS |
|
|
Image Classification (Q)
|
99% |
55
10.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
44
0.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
44
0.71 IPS |
|
|
Image Segmentation (Q)
|
98% |
65
1.06 IPS |
|
|
Pose Estimation (SP)
|
100% |
47
0.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
49
0.06 IPS |
|
|
Pose Estimation (Q)
|
98% |
118
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
32
2.56 IPS |
|
|
Object Detection (HP)
|
100% |
33
2.58 IPS |
|
|
Object Detection (Q)
|
87% |
56
4.47 IPS |
|
|
Face Detection (SP)
|
100% |
81
0.96 IPS |
|
|
Face Detection (HP)
|
100% |
81
0.97 IPS |
|
|
Face Detection (Q)
|
97% |
138
1.65 IPS |
|
|
Depth Estimation (SP)
|
100% |
64
0.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
64
0.49 IPS |
|
|
Depth Estimation (Q)
|
64% |
112
1.02 IPS |
|
|
Style Transfer (SP)
|
100% |
118
0.15 IPS |
|
|
Style Transfer (HP)
|
100% |
116
0.15 IPS |
|
|
Style Transfer (Q)
|
98% |
263
0.34 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
36
1.33 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
36
1.34 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
72
2.66 IPS |
|
|
Text Classification (SP)
|
100% |
45
59.7 IPS |
|
|
Text Classification (HP)
|
100% |
45
60.3 IPS |
|
|
Text Classification (Q)
|
91% |
65
88.0 IPS |
|
|
Machine Translation (SP)
|
100% |
75
1.30 IPS |
|
|
Machine Translation (HP)
|
100% |
78
1.35 IPS |
|
|
Machine Translation (Q)
|
57% |
58
1.42 IPS |
