iPhone X
Geekbench ML Score
636
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 04 2025 07:46 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
189
35.3 IPS |
|
|
Image Classification (F16)
|
100% |
147
27.5 IPS |
|
|
Image Classification (I8)
|
99% |
174
32.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
2326
2.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
2804
3.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
2683
3.25 IPS |
|
|
Object Detection (F32)
|
100% |
337
25.2 IPS |
|
|
Object Detection (F16)
|
100% |
276
20.6 IPS |
|
|
Object Detection (I8)
|
97% |
265
19.8 IPS |
|
|
Face Detection (F32)
|
100% |
956
11.4 IPS |
|
|
Face Detection (F16)
|
100% |
1015
12.1 IPS |
|
|
Face Detection (I8)
|
99% |
1003
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2179
16.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2589
20.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
2754
21.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4372
5.75 IPS |
|
|
Style Transfer (F16)
|
100% |
5071
6.67 IPS |
|
|
Style Transfer (I8)
|
100% |
4949
6.51 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1050
37.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
992
35.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
910
32.5 IPS |
|
|
Text Classification (F32)
|
100% |
55
78.4 IPS |
|
|
Text Classification (F16)
|
100% |
198
285.1 IPS |
|
|
Text Classification (I8)
|
96% |
201
288.6 IPS |
|
|
Machine Translation (F32)
|
100% |
313
5.76 IPS |
|
|
Machine Translation (F16)
|
100% |
245
4.50 IPS |
|
|
Machine Translation (I8)
|
99% |
313
5.77 IPS |
