iPhone X
Geekbench ML Score
643
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | December 02 2024 12:44 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.10 |
| 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% |
177
33.2 IPS |
|
|
Image Classification (F16)
|
100% |
149
27.9 IPS |
|
|
Image Classification (I8)
|
99% |
149
27.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
200
3.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
2307
2.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
2822
3.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
2722
3.30 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
328
24.5 IPS |
|
|
Object Detection (I8)
|
97% |
334
24.9 IPS |
|
|
Face Detection (F32)
|
100% |
908
10.8 IPS |
|
|
Face Detection (F16)
|
100% |
966
11.5 IPS |
|
|
Face Detection (I8)
|
99% |
996
11.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
2245
17.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2602
20.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
2431
18.9 IPS |
|
|
Style Transfer (F32)
|
100% |
4435
5.83 IPS |
|
|
Style Transfer (F16)
|
100% |
5061
6.66 IPS |
|
|
Style Transfer (I8)
|
100% |
5024
6.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1118
39.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1210
43.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1105
39.5 IPS |
|
|
Text Classification (F32)
|
100% |
53
75.8 IPS |
|
|
Text Classification (F16)
|
100% |
199
286.1 IPS |
|
|
Text Classification (I8)
|
96% |
201
288.6 IPS |
|
|
Machine Translation (F32)
|
100% |
312
5.74 IPS |
|
|
Machine Translation (F16)
|
100% |
240
4.41 IPS |
|
|
Machine Translation (I8)
|
99% |
299
5.50 IPS |
