iPhone X
Geekbench ML Score
630
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | February 14 2025 05:34 PM |
| Views | 13 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
179
33.5 IPS |
|
|
Image Classification (F16)
|
100% |
142
26.6 IPS |
|
|
Image Classification (I8)
|
99% |
143
26.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
202
3.37 IPS |
|
|
Pose Estimation (F32)
|
100% |
2303
2.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
2659
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2651
3.21 IPS |
|
|
Object Detection (F32)
|
100% |
298
22.3 IPS |
|
|
Object Detection (F16)
|
100% |
343
25.6 IPS |
|
|
Object Detection (I8)
|
97% |
284
21.2 IPS |
|
|
Face Detection (F32)
|
100% |
970
11.5 IPS |
|
|
Face Detection (F16)
|
100% |
978
11.6 IPS |
|
|
Face Detection (I8)
|
99% |
944
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2298
17.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2616
20.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
2434
18.9 IPS |
|
|
Style Transfer (F32)
|
100% |
4317
5.68 IPS |
|
|
Style Transfer (F16)
|
100% |
4770
6.27 IPS |
|
|
Style Transfer (I8)
|
100% |
4836
6.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1003
35.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
998
35.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1067
38.1 IPS |
|
|
Text Classification (F32)
|
100% |
51
72.8 IPS |
|
|
Text Classification (F16)
|
100% |
202
289.6 IPS |
|
|
Text Classification (I8)
|
96% |
196
281.4 IPS |
|
|
Machine Translation (F32)
|
100% |
326
5.99 IPS |
|
|
Machine Translation (F16)
|
100% |
253
4.66 IPS |
|
|
Machine Translation (I8)
|
99% |
323
5.95 IPS |
