HMD Global Nokia C300
Geekbench ML Score
216
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 12:16 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HMD Global Nokia C300 |
| Model ID | HMD Global Nokia C300 |
| Motherboard | Orion |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 2.61 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
113
21.1 IPS |
|
|
Image Classification (F16)
|
100% |
115
21.5 IPS |
|
|
Image Classification (I8)
|
97% |
177
33.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
166
2.76 IPS |
|
|
Image Segmentation (F16)
|
100% |
167
2.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
182
3.05 IPS |
|
|
Pose Estimation (F32)
|
100% |
194
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
196
0.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
677
0.82 IPS |
|
|
Object Detection (F32)
|
100% |
127
9.49 IPS |
|
|
Object Detection (F16)
|
100% |
127
9.50 IPS |
|
|
Object Detection (I8)
|
61% |
206
15.4 IPS |
|
|
Face Detection (F32)
|
100% |
254
3.02 IPS |
|
|
Face Detection (F16)
|
100% |
256
3.04 IPS |
|
|
Face Detection (I8)
|
86% |
453
5.39 IPS |
|
|
Depth Estimation (F32)
|
100% |
227
1.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
225
1.74 IPS |
|
|
Depth Estimation (I8)
|
95% |
443
3.44 IPS |
|
|
Style Transfer (F32)
|
100% |
343
0.45 IPS |
|
|
Style Transfer (F16)
|
100% |
259
0.34 IPS |
|
|
Style Transfer (I8)
|
98% |
877
1.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
150
5.36 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
152
5.42 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
326
11.6 IPS |
|
|
Text Classification (F32)
|
100% |
160
229.9 IPS |
|
|
Text Classification (F16)
|
100% |
153
219.4 IPS |
|
|
Text Classification (I8)
|
92% |
128
184.3 IPS |
|
|
Machine Translation (F32)
|
100% |
277
5.09 IPS |
|
|
Machine Translation (F16)
|
100% |
264
4.85 IPS |
|
|
Machine Translation (I8)
|
64% |
133
2.45 IPS |
