iPhone 8
Geekbench ML Score
611
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 01 2024 08:20 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.10 |
| Model | iPhone 8 |
| Model ID | iPhone10,1 |
| Motherboard | D20AP |
| CPU Information | |
|---|---|
| Name | Apple A11 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.39 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 48.0 KB x 1 |
| L1 Data Cache | 32.0 KB x 1 |
| L2 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 1.93 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
176
33.0 IPS |
|
|
Image Classification (F16)
|
100% |
146
27.4 IPS |
|
|
Image Classification (I8)
|
99% |
142
26.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
189
3.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
197
3.29 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
2125
2.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
2379
2.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
2201
2.66 IPS |
|
|
Object Detection (F32)
|
100% |
290
21.6 IPS |
|
|
Object Detection (F16)
|
100% |
346
25.8 IPS |
|
|
Object Detection (I8)
|
97% |
289
21.6 IPS |
|
|
Face Detection (F32)
|
100% |
985
11.7 IPS |
|
|
Face Detection (F16)
|
100% |
958
11.4 IPS |
|
|
Face Detection (I8)
|
99% |
939
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2160
16.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2514
19.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
2411
18.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4360
5.74 IPS |
|
|
Style Transfer (F16)
|
100% |
4942
6.50 IPS |
|
|
Style Transfer (I8)
|
100% |
4922
6.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1029
36.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1043
37.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1035
37.0 IPS |
|
|
Text Classification (F32)
|
100% |
50
71.2 IPS |
|
|
Text Classification (F16)
|
100% |
202
290.3 IPS |
|
|
Text Classification (I8)
|
96% |
199
285.5 IPS |
|
|
Machine Translation (F32)
|
100% |
308
5.66 IPS |
|
|
Machine Translation (F16)
|
100% |
217
3.99 IPS |
|
|
Machine Translation (I8)
|
99% |
249
4.58 IPS |
