iPhone X
Geekbench ML Score
202
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 25 2025 05:25 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.11 |
| 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% |
132
24.7 IPS |
|
|
Image Classification (F16)
|
100% |
119
22.3 IPS |
|
|
Image Classification (I8)
|
99% |
140
26.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
142
2.36 IPS |
|
|
Image Segmentation (F16)
|
100% |
140
2.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
140
2.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
541
0.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
550
0.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
546
0.66 IPS |
|
|
Object Detection (F32)
|
100% |
145
10.8 IPS |
|
|
Object Detection (F16)
|
100% |
131
9.81 IPS |
|
|
Object Detection (I8)
|
97% |
163
12.2 IPS |
|
|
Face Detection (F32)
|
100% |
358
4.25 IPS |
|
|
Face Detection (F16)
|
100% |
354
4.21 IPS |
|
|
Face Detection (I8)
|
99% |
278
3.30 IPS |
|
|
Depth Estimation (F32)
|
100% |
342
2.66 IPS |
|
|
Depth Estimation (F16)
|
100% |
318
2.46 IPS |
|
|
Depth Estimation (I8)
|
99% |
276
2.14 IPS |
|
|
Style Transfer (F32)
|
100% |
546
0.72 IPS |
|
|
Style Transfer (F16)
|
100% |
550
0.72 IPS |
|
|
Style Transfer (I8)
|
100% |
481
0.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
179
6.39 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
157
5.62 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
177
6.32 IPS |
|
|
Text Classification (F32)
|
100% |
56
81.2 IPS |
|
|
Text Classification (F16)
|
100% |
82
117.7 IPS |
|
|
Text Classification (I8)
|
96% |
99
142.7 IPS |
|
|
Machine Translation (F32)
|
100% |
151
2.78 IPS |
|
|
Machine Translation (F16)
|
100% |
90
1.66 IPS |
|
|
Machine Translation (I8)
|
99% |
105
1.93 IPS |
