Google octopus
Geekbench AI Score
11
Single Precision Score
11
Half Precision Score
6
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 05 2025 01:04 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | placeholder |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google octopus |
| Model ID | Google octopus |
| Motherboard | apel |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 2 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 3.12 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
936.5 IPS |
|
|
Image Classification (HP)
|
0% |
0
1.16 KIPS |
|
|
Image Classification (Q)
|
0% |
0
1.06 KIPS |
|
|
Image Segmentation (SP)
|
73% |
7022
121.4 IPS |
|
|
Image Segmentation (HP)
|
73% |
6754
116.7 IPS |
|
|
Image Segmentation (Q)
|
73% |
13259
229.1 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
291.0 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
309.7 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
852.1 IPS |
|
|
Object Detection (SP)
|
0% |
0
461.5 IPS |
|
|
Object Detection (HP)
|
0% |
0
471.4 IPS |
|
|
Object Detection (Q)
|
0% |
0
328.7 IPS |
|
|
Face Detection (SP)
|
0% |
0
140.3 IPS |
|
|
Face Detection (HP)
|
0% |
0
142.7 IPS |
|
|
Face Detection (Q)
|
0% |
0
221.0 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
316.8 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
315.7 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
287.0 IPS |
|
|
Style Transfer (SP)
|
32% |
58882
738.5 IPS |
|
|
Style Transfer (HP)
|
32% |
44281
555.4 IPS |
|
|
Style Transfer (Q)
|
0% |
0
1.80 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
729.3 IPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
717.8 IPS |
|
|
Image Super-Resolution (Q)
|
2% |
75
881.2 IPS |
|
|
Text Classification (SP)
|
29% |
123
2.13 KIPS |
|
|
Text Classification (HP)
|
29% |
120
2.07 KIPS |
|
|
Text Classification (Q)
|
29% |
94
1.62 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
2.85 IPS |
|
|
Machine Translation (HP)
|
0% |
0
2.78 IPS |
|
|
Machine Translation (Q)
|
0% |
0
2.09 IPS |
