iPhone X
Geekbench ML Score
639
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 29 2025 03:34 AM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.12 |
| Model | iPhone X |
| Model ID | iPhone10,3 |
| Motherboard | D22AP |
| 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% |
185
34.6 IPS |
|
|
Image Classification (F16)
|
100% |
153
28.7 IPS |
|
|
Image Classification (I8)
|
99% |
153
28.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
200
3.35 IPS |
|
|
Pose Estimation (F32)
|
100% |
2347
2.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
2733
3.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
2672
3.24 IPS |
|
|
Object Detection (F32)
|
100% |
365
27.2 IPS |
|
|
Object Detection (F16)
|
100% |
304
22.7 IPS |
|
|
Object Detection (I8)
|
97% |
270
20.2 IPS |
|
|
Face Detection (F32)
|
100% |
988
11.7 IPS |
|
|
Face Detection (F16)
|
100% |
1112
13.2 IPS |
|
|
Face Detection (I8)
|
99% |
959
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2281
17.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2504
19.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
2451
19.0 IPS |
|
|
Style Transfer (F32)
|
100% |
4638
6.10 IPS |
|
|
Style Transfer (F16)
|
100% |
5254
6.91 IPS |
|
|
Style Transfer (I8)
|
100% |
5117
6.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
929
33.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1032
36.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1045
37.3 IPS |
|
|
Text Classification (F32)
|
100% |
50
72.0 IPS |
|
|
Text Classification (F16)
|
100% |
194
278.5 IPS |
|
|
Text Classification (I8)
|
96% |
197
283.2 IPS |
|
|
Machine Translation (F32)
|
100% |
319
5.87 IPS |
|
|
Machine Translation (F16)
|
100% |
250
4.59 IPS |
|
|
Machine Translation (I8)
|
99% |
319
5.88 IPS |
