Google rammus
Geekbench AI Score
86
Single Precision Score
87
Half Precision Score
41
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 08 2025 06:35 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | placeholder |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google rammus |
| Model ID | Google rammus |
| Motherboard | shyvana |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 6.96 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
52
9.59 IPS |
|
|
Image Classification (HP)
|
100% |
53
9.82 IPS |
|
|
Image Classification (Q)
|
99% |
24
4.56 IPS |
|
|
Image Segmentation (SP)
|
100% |
68
1.10 IPS |
|
|
Image Segmentation (HP)
|
100% |
71
1.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
31
0.50 IPS |
|
|
Pose Estimation (SP)
|
100% |
90
0.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
90
0.10 IPS |
|
|
Pose Estimation (Q)
|
98% |
55
0.06 IPS |
|
|
Object Detection (SP)
|
100% |
47
3.75 IPS |
|
|
Object Detection (HP)
|
100% |
51
4.05 IPS |
|
|
Object Detection (Q)
|
87% |
26
2.06 IPS |
|
|
Face Detection (SP)
|
100% |
148
1.76 IPS |
|
|
Face Detection (HP)
|
100% |
155
1.84 IPS |
|
|
Face Detection (Q)
|
97% |
53
0.64 IPS |
|
|
Depth Estimation (SP)
|
100% |
119
0.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
121
0.93 IPS |
|
|
Depth Estimation (Q)
|
64% |
56
0.51 IPS |
|
|
Style Transfer (SP)
|
100% |
215
0.28 IPS |
|
|
Style Transfer (HP)
|
100% |
209
0.27 IPS |
|
|
Style Transfer (Q)
|
98% |
150
0.19 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
52
1.93 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51
1.90 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
33
1.21 IPS |
|
|
Text Classification (SP)
|
100% |
68
90.4 IPS |
|
|
Text Classification (HP)
|
100% |
69
91.5 IPS |
|
|
Text Classification (Q)
|
91% |
31
41.2 IPS |
|
|
Machine Translation (SP)
|
100% |
113
1.94 IPS |
|
|
Machine Translation (HP)
|
100% |
115
1.99 IPS |
|
|
Machine Translation (Q)
|
57% |
34
0.84 IPS |
