iPhone 11 Pro
Geekbench ML Score
1807
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | saiht |
| Upload Date | July 25 2024 12:33 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 11 Pro |
| Model ID | iPhone12,3 |
| Motherboard | D421AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.68 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
293
54.8 IPS |
|
|
Image Classification (F16)
|
100% |
2894
541.5 IPS |
|
|
Image Classification (I8)
|
99% |
2910
544.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
220
3.68 IPS |
|
|
Image Segmentation (F16)
|
100% |
331
5.53 IPS |
|
|
Image Segmentation (I8)
|
100% |
334
5.57 IPS |
|
|
Pose Estimation (F32)
|
100% |
2282
2.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
26071
31.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
26163
31.7 IPS |
|
|
Object Detection (F32)
|
100% |
563
42.0 IPS |
|
|
Object Detection (F16)
|
100% |
1298
96.9 IPS |
|
|
Object Detection (I8)
|
97% |
538
40.2 IPS |
|
|
Face Detection (F32)
|
100% |
2495
29.7 IPS |
|
|
Face Detection (F16)
|
98% |
5217
62.0 IPS |
|
|
Face Detection (I8)
|
97% |
5157
61.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
2512
19.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
20947
162.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
23484
182.1 IPS |
|
|
Style Transfer (F32)
|
100% |
5922
7.79 IPS |
|
|
Style Transfer (F16)
|
100% |
19333
25.4 IPS |
|
|
Style Transfer (I8)
|
100% |
19259
25.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1136
40.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5403
192.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5616
200.6 IPS |
|
|
Text Classification (F32)
|
100% |
236
338.8 IPS |
|
|
Text Classification (F16)
|
100% |
311
446.6 IPS |
|
|
Text Classification (I8)
|
96% |
313
449.3 IPS |
|
|
Machine Translation (F32)
|
100% |
216
3.97 IPS |
|
|
Machine Translation (F16)
|
100% |
203
3.74 IPS |
|
|
Machine Translation (I8)
|
99% |
221
4.06 IPS |
