iPhone X
Geekbench ML Score
643
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 01 2025 08:06 AM |
| Views | 7 |
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% |
178
33.2 IPS |
|
|
Image Classification (F16)
|
100% |
150
28.0 IPS |
|
|
Image Classification (I8)
|
99% |
150
28.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
100% |
198
3.31 IPS |
|
|
Pose Estimation (F32)
|
100% |
2340
2.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
2872
3.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
2710
3.28 IPS |
|
|
Object Detection (F32)
|
100% |
355
26.5 IPS |
|
|
Object Detection (F16)
|
100% |
320
23.9 IPS |
|
|
Object Detection (I8)
|
97% |
309
23.1 IPS |
|
|
Face Detection (F32)
|
100% |
991
11.8 IPS |
|
|
Face Detection (F16)
|
100% |
924
11.0 IPS |
|
|
Face Detection (I8)
|
99% |
901
10.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2289
17.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2611
20.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
2520
19.5 IPS |
|
|
Style Transfer (F32)
|
100% |
4695
6.18 IPS |
|
|
Style Transfer (F16)
|
100% |
4927
6.48 IPS |
|
|
Style Transfer (I8)
|
100% |
4794
6.31 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1252
44.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1193
42.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1169
41.7 IPS |
|
|
Text Classification (F32)
|
100% |
53
76.9 IPS |
|
|
Text Classification (F16)
|
100% |
199
286.0 IPS |
|
|
Text Classification (I8)
|
96% |
197
283.4 IPS |
|
|
Machine Translation (F32)
|
100% |
279
5.14 IPS |
|
|
Machine Translation (F16)
|
100% |
234
4.30 IPS |
|
|
Machine Translation (I8)
|
99% |
299
5.49 IPS |
