iPhone X
Geekbench ML Score
432
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 31 2025 03:11 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.12 |
| 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% |
235
44.0 IPS |
|
|
Image Classification (F16)
|
100% |
217
40.6 IPS |
|
|
Image Classification (I8)
|
99% |
218
40.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
203
3.39 IPS |
|
|
Image Segmentation (F16)
|
100% |
209
3.48 IPS |
|
|
Image Segmentation (I8)
|
100% |
207
3.45 IPS |
|
|
Pose Estimation (F32)
|
100% |
1088
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
1054
1.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
1059
1.28 IPS |
|
|
Object Detection (F32)
|
100% |
260
19.4 IPS |
|
|
Object Detection (F16)
|
100% |
246
18.3 IPS |
|
|
Object Detection (I8)
|
97% |
261
19.5 IPS |
|
|
Face Detection (F32)
|
100% |
476
5.66 IPS |
|
|
Face Detection (F16)
|
100% |
471
5.59 IPS |
|
|
Face Detection (I8)
|
99% |
470
5.59 IPS |
|
|
Depth Estimation (F32)
|
100% |
639
4.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
590
4.57 IPS |
|
|
Depth Estimation (I8)
|
99% |
587
4.55 IPS |
|
|
Style Transfer (F32)
|
100% |
1801
2.37 IPS |
|
|
Style Transfer (F16)
|
100% |
1814
2.39 IPS |
|
|
Style Transfer (I8)
|
100% |
1843
2.42 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
560
20.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
571
20.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
576
20.6 IPS |
|
|
Text Classification (F32)
|
100% |
245
352.1 IPS |
|
|
Text Classification (F16)
|
100% |
216
310.5 IPS |
|
|
Text Classification (I8)
|
96% |
221
317.4 IPS |
|
|
Machine Translation (F32)
|
100% |
297
5.47 IPS |
|
|
Machine Translation (F16)
|
100% |
239
4.40 IPS |
|
|
Machine Translation (I8)
|
99% |
280
5.15 IPS |
