iPhone X
Geekbench ML Score
642
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 21 2024 11:07 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.8 |
| Model | iPhone X |
| Model ID | iPhone10,6 |
| Motherboard | D221AP |
| 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 | 2.76 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
27.3 IPS |
|
|
Image Classification (I8)
|
99% |
149
27.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
201
3.36 IPS |
|
|
Image Segmentation (I8)
|
100% |
201
3.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
2315
2.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
2884
3.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
2864
3.47 IPS |
|
|
Object Detection (F32)
|
100% |
295
22.0 IPS |
|
|
Object Detection (F16)
|
100% |
329
24.5 IPS |
|
|
Object Detection (I8)
|
97% |
255
19.1 IPS |
|
|
Face Detection (F32)
|
100% |
973
11.6 IPS |
|
|
Face Detection (F16)
|
100% |
955
11.4 IPS |
|
|
Face Detection (I8)
|
99% |
1066
12.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2235
17.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2484
19.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
2753
21.3 IPS |
|
|
Style Transfer (F32)
|
100% |
4965
6.53 IPS |
|
|
Style Transfer (F16)
|
100% |
4991
6.56 IPS |
|
|
Style Transfer (I8)
|
100% |
4973
6.54 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1125
40.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1212
43.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1027
36.7 IPS |
|
|
Text Classification (F32)
|
100% |
52
75.1 IPS |
|
|
Text Classification (F16)
|
100% |
197
283.1 IPS |
|
|
Text Classification (I8)
|
96% |
196
282.3 IPS |
|
|
Machine Translation (F32)
|
100% |
313
5.76 IPS |
|
|
Machine Translation (F16)
|
100% |
247
4.54 IPS |
|
|
Machine Translation (I8)
|
99% |
313
5.75 IPS |
