iPhone X 超冷却 iPhone X
Geekbench ML Score
627
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | SyameimaruKoa |
| Upload Date | September 29 2025 03:45 AM |
| Views | 13 |
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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
176
33.0 IPS |
|
|
Image Classification (F16)
|
100% |
145
27.1 IPS |
|
|
Image Classification (I8)
|
99% |
145
27.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.12 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.32 IPS |
|
|
Image Segmentation (I8)
|
100% |
200
3.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
2302
2.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
2827
3.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
2711
3.28 IPS |
|
|
Object Detection (F32)
|
100% |
263
19.6 IPS |
|
|
Object Detection (F16)
|
100% |
276
20.6 IPS |
|
|
Object Detection (I8)
|
97% |
309
23.1 IPS |
|
|
Face Detection (F32)
|
100% |
901
10.7 IPS |
|
|
Face Detection (F16)
|
100% |
958
11.4 IPS |
|
|
Face Detection (I8)
|
99% |
980
11.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2230
17.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2451
19.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
2559
19.8 IPS |
|
|
Style Transfer (F32)
|
100% |
4429
5.83 IPS |
|
|
Style Transfer (F16)
|
100% |
4802
6.32 IPS |
|
|
Style Transfer (I8)
|
100% |
4805
6.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1234
44.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
992
35.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1056
37.7 IPS |
|
|
Text Classification (F32)
|
100% |
51
72.6 IPS |
|
|
Text Classification (F16)
|
100% |
192
276.1 IPS |
|
|
Text Classification (I8)
|
96% |
200
287.1 IPS |
|
|
Machine Translation (F32)
|
100% |
322
5.92 IPS |
|
|
Machine Translation (F16)
|
100% |
251
4.62 IPS |
|
|
Machine Translation (I8)
|
99% |
320
5.88 IPS |
