Raspberry Raspberry Pi 5
Geekbench ML Score
192
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 07 2024 12:33 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Raspberry Raspberry Pi 5 |
| Model ID | Raspberry Raspberry Pi 5 |
| Motherboard | |
| Governor | ondemand |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.88 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
94
17.6 IPS |
|
|
Image Classification (F16)
|
100% |
96
17.9 IPS |
|
|
Image Classification (I8)
|
97% |
237
44.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
125
2.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
124
2.08 IPS |
|
|
Image Segmentation (I8)
|
98% |
273
4.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
162
0.20 IPS |
|
|
Pose Estimation (F16)
|
100% |
163
0.20 IPS |
|
|
Pose Estimation (I8)
|
100% |
567
0.69 IPS |
|
|
Object Detection (F32)
|
100% |
98
7.31 IPS |
|
|
Object Detection (F16)
|
100% |
98
7.28 IPS |
|
|
Object Detection (I8)
|
61% |
261
19.5 IPS |
|
|
Face Detection (F32)
|
100% |
195
2.32 IPS |
|
|
Face Detection (F16)
|
100% |
188
2.24 IPS |
|
|
Face Detection (I8)
|
86% |
519
6.17 IPS |
|
|
Depth Estimation (F32)
|
100% |
163
1.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
164
1.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
479
3.71 IPS |
|
|
Style Transfer (F32)
|
100% |
238
0.31 IPS |
|
|
Style Transfer (F16)
|
100% |
241
0.32 IPS |
|
|
Style Transfer (I8)
|
98% |
767
1.01 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
82
2.94 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
83
2.95 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
365
13.0 IPS |
|
|
Text Classification (F32)
|
100% |
138
198.3 IPS |
|
|
Text Classification (F16)
|
100% |
138
197.6 IPS |
|
|
Text Classification (I8)
|
92% |
272
390.6 IPS |
|
|
Machine Translation (F32)
|
100% |
199
3.67 IPS |
|
|
Machine Translation (F16)
|
100% |
175
3.22 IPS |
|
|
Machine Translation (I8)
|
64% |
224
4.12 IPS |
