iPhone X
Geekbench ML Score
647
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 07 2025 10:25 AM |
| Views | 3 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.9 IPS |
|
|
Image Classification (F16)
|
100% |
146
27.3 IPS |
|
|
Image Classification (I8)
|
99% |
146
27.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
202
3.37 IPS |
|
|
Image Segmentation (I8)
|
100% |
203
3.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
2316
2.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
2728
3.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
2865
3.47 IPS |
|
|
Object Detection (F32)
|
100% |
331
24.7 IPS |
|
|
Object Detection (F16)
|
100% |
323
24.1 IPS |
|
|
Object Detection (I8)
|
97% |
268
20.0 IPS |
|
|
Face Detection (F32)
|
100% |
984
11.7 IPS |
|
|
Face Detection (F16)
|
100% |
974
11.6 IPS |
|
|
Face Detection (I8)
|
99% |
919
10.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2469
19.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2815
21.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
2835
22.0 IPS |
|
|
Style Transfer (F32)
|
100% |
4523
5.95 IPS |
|
|
Style Transfer (F16)
|
100% |
5525
7.27 IPS |
|
|
Style Transfer (I8)
|
100% |
5161
6.79 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1115
39.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1095
39.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1084
38.7 IPS |
|
|
Text Classification (F32)
|
100% |
53
75.9 IPS |
|
|
Text Classification (F16)
|
100% |
192
276.6 IPS |
|
|
Text Classification (I8)
|
96% |
195
280.9 IPS |
|
|
Machine Translation (F32)
|
100% |
311
5.72 IPS |
|
|
Machine Translation (F16)
|
100% |
241
4.44 IPS |
|
|
Machine Translation (I8)
|
99% |
310
5.71 IPS |
