iPhone X
Geekbench ML Score
434
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 05 2024 07:08 PM |
| 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% |
239
44.8 IPS |
|
|
Image Classification (F16)
|
100% |
223
41.7 IPS |
|
|
Image Classification (I8)
|
99% |
221
41.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
207
3.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
213
3.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
212
3.53 IPS |
|
|
Pose Estimation (F32)
|
100% |
1100
1.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
1057
1.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
1070
1.30 IPS |
|
|
Object Detection (F32)
|
100% |
249
18.6 IPS |
|
|
Object Detection (F16)
|
100% |
247
18.4 IPS |
|
|
Object Detection (I8)
|
97% |
269
20.0 IPS |
|
|
Face Detection (F32)
|
100% |
481
5.72 IPS |
|
|
Face Detection (F16)
|
100% |
474
5.64 IPS |
|
|
Face Detection (I8)
|
99% |
473
5.62 IPS |
|
|
Depth Estimation (F32)
|
100% |
622
4.82 IPS |
|
|
Depth Estimation (F16)
|
100% |
578
4.48 IPS |
|
|
Depth Estimation (I8)
|
99% |
582
4.51 IPS |
|
|
Style Transfer (F32)
|
100% |
1743
2.29 IPS |
|
|
Style Transfer (F16)
|
100% |
1713
2.25 IPS |
|
|
Style Transfer (I8)
|
100% |
1709
2.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
560
20.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
573
20.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
573
20.5 IPS |
|
|
Text Classification (F32)
|
100% |
257
369.9 IPS |
|
|
Text Classification (F16)
|
100% |
212
304.7 IPS |
|
|
Text Classification (I8)
|
96% |
220
315.5 IPS |
|
|
Machine Translation (F32)
|
100% |
294
5.40 IPS |
|
|
Machine Translation (F16)
|
100% |
259
4.76 IPS |
|
|
Machine Translation (I8)
|
99% |
314
5.78 IPS |
