iPhone X
Geekbench ML Score
352
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 04 2025 07:52 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.10 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
232
43.4 IPS |
|
|
Image Classification (F16)
|
100% |
215
40.2 IPS |
|
|
Image Classification (I8)
|
99% |
214
40.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
204
3.40 IPS |
|
|
Image Segmentation (F16)
|
100% |
204
3.41 IPS |
|
|
Image Segmentation (I8)
|
100% |
201
3.35 IPS |
|
|
Pose Estimation (F32)
|
100% |
1043
1.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
1022
1.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
1015
1.23 IPS |
|
|
Object Detection (F32)
|
100% |
236
17.6 IPS |
|
|
Object Detection (F16)
|
100% |
227
17.0 IPS |
|
|
Object Detection (I8)
|
97% |
251
18.8 IPS |
|
|
Face Detection (F32)
|
100% |
481
5.72 IPS |
|
|
Face Detection (F16)
|
100% |
468
5.57 IPS |
|
|
Face Detection (I8)
|
99% |
443
5.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
565
4.38 IPS |
|
|
Depth Estimation (F16)
|
100% |
457
3.54 IPS |
|
|
Depth Estimation (I8)
|
99% |
429
3.33 IPS |
|
|
Style Transfer (F32)
|
100% |
1230
1.62 IPS |
|
|
Style Transfer (F16)
|
100% |
1054
1.39 IPS |
|
|
Style Transfer (I8)
|
100% |
1043
1.37 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
318
11.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
315
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
327
11.7 IPS |
|
|
Text Classification (F32)
|
100% |
151
216.4 IPS |
|
|
Text Classification (F16)
|
100% |
150
216.2 IPS |
|
|
Text Classification (I8)
|
96% |
151
217.2 IPS |
|
|
Machine Translation (F32)
|
100% |
254
4.67 IPS |
|
|
Machine Translation (F16)
|
100% |
198
3.64 IPS |
|
|
Machine Translation (I8)
|
99% |
238
4.39 IPS |
