Nintendo Switch
Geekbench AI Score
10
Single Precision Score
10
Half Precision Score
6
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | TheDogDR |
| Upload Date | January 31 2025 07:02 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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)
|
0% |
0
754.0 IPS |
|
|
Image Classification (HP)
|
0% |
0
728.7 IPS |
|
|
Image Classification (Q)
|
0% |
0
987.3 IPS |
|
|
Image Segmentation (SP)
|
73% |
2762
47.7 IPS |
|
|
Image Segmentation (HP)
|
73% |
2791
48.2 IPS |
|
|
Image Segmentation (Q)
|
73% |
8549
147.7 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
208.6 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
216.6 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
600.3 IPS |
|
|
Object Detection (SP)
|
0% |
0
297.6 IPS |
|
|
Object Detection (HP)
|
0% |
0
284.4 IPS |
|
|
Object Detection (Q)
|
0% |
0
229.9 IPS |
|
|
Face Detection (SP)
|
0% |
0
89.0 IPS |
|
|
Face Detection (HP)
|
0% |
0
88.0 IPS |
|
|
Face Detection (Q)
|
0% |
0
178.7 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
259.9 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
256.6 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
225.9 IPS |
|
|
Style Transfer (SP)
|
32% |
30192
378.7 IPS |
|
|
Style Transfer (HP)
|
32% |
30570
383.4 IPS |
|
|
Style Transfer (Q)
|
0% |
0
1.22 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
553.8 IPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
565.3 IPS |
|
|
Image Super-Resolution (Q)
|
2% |
83
974.5 IPS |
|
|
Text Classification (SP)
|
29% |
189
3.27 KIPS |
|
|
Text Classification (HP)
|
29% |
188
3.26 KIPS |
|
|
Text Classification (Q)
|
29% |
124
2.14 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
1.73 IPS |
|
|
Machine Translation (HP)
|
0% |
0
1.71 IPS |
|
|
Machine Translation (Q)
|
0% |
0
1.45 IPS |
