iPhone 11 Pro Max
Geekbench ML Score
1702
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 27 2024 01:40 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPhone 11 Pro Max |
| Model ID | iPhone12,5 |
| Motherboard | D431AP |
| 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 | 3.66 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
277
51.7 IPS |
|
|
Image Classification (F16)
|
100% |
2620
490.2 IPS |
|
|
Image Classification (I8)
|
99% |
2651
496.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
227
3.79 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
334
5.57 IPS |
|
|
Pose Estimation (F32)
|
100% |
2259
2.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
25975
31.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
25304
30.6 IPS |
|
|
Object Detection (F32)
|
100% |
399
29.8 IPS |
|
|
Object Detection (F16)
|
100% |
1140
85.1 IPS |
|
|
Object Detection (I8)
|
97% |
398
29.7 IPS |
|
|
Face Detection (F32)
|
100% |
2489
29.6 IPS |
|
|
Face Detection (F16)
|
98% |
4832
57.4 IPS |
|
|
Face Detection (I8)
|
97% |
4805
57.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2473
19.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
20582
159.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
20465
158.7 IPS |
|
|
Style Transfer (F32)
|
100% |
5845
7.69 IPS |
|
|
Style Transfer (F16)
|
100% |
17794
23.4 IPS |
|
|
Style Transfer (I8)
|
100% |
17565
23.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1030
36.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5052
180.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5223
186.5 IPS |
|
|
Text Classification (F32)
|
100% |
234
336.4 IPS |
|
|
Text Classification (F16)
|
100% |
307
440.8 IPS |
|
|
Text Classification (I8)
|
96% |
311
446.3 IPS |
|
|
Machine Translation (F32)
|
100% |
220
4.05 IPS |
|
|
Machine Translation (F16)
|
100% |
206
3.79 IPS |
|
|
Machine Translation (I8)
|
99% |
216
3.97 IPS |
