iPhone 11 Pro Max
Geekbench ML Score
1727
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 27 2024 01:58 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% |
274
51.3 IPS |
|
|
Image Classification (F16)
|
100% |
2648
495.4 IPS |
|
|
Image Classification (I8)
|
99% |
2613
489.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
239
3.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
333
5.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
2258
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
24926
30.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
25783
31.2 IPS |
|
|
Object Detection (F32)
|
100% |
465
34.8 IPS |
|
|
Object Detection (F16)
|
100% |
1124
83.9 IPS |
|
|
Object Detection (I8)
|
97% |
475
35.4 IPS |
|
|
Face Detection (F32)
|
100% |
2524
30.0 IPS |
|
|
Face Detection (F16)
|
98% |
4844
57.6 IPS |
|
|
Face Detection (I8)
|
97% |
4811
57.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2492
19.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
21029
163.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
20840
161.6 IPS |
|
|
Style Transfer (F32)
|
100% |
5929
7.80 IPS |
|
|
Style Transfer (F16)
|
100% |
18028
23.7 IPS |
|
|
Style Transfer (I8)
|
100% |
17819
23.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1174
41.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5326
190.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5249
187.4 IPS |
|
|
Text Classification (F32)
|
100% |
228
328.3 IPS |
|
|
Text Classification (F16)
|
100% |
297
427.1 IPS |
|
|
Text Classification (I8)
|
96% |
294
422.4 IPS |
|
|
Machine Translation (F32)
|
100% |
212
3.89 IPS |
|
|
Machine Translation (F16)
|
100% |
203
3.74 IPS |
|
|
Machine Translation (I8)
|
99% |
213
3.92 IPS |
