iPhone 11 Pro Max
Geekbench ML Score
1730
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 19 2024 04:16 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
272
50.8 IPS |
|
|
Image Classification (F16)
|
100% |
2650
495.9 IPS |
|
|
Image Classification (I8)
|
99% |
2681
501.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
229
3.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
333
5.57 IPS |
|
|
Pose Estimation (F32)
|
100% |
2258
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
25260
30.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
25518
30.9 IPS |
|
|
Object Detection (F32)
|
100% |
500
37.4 IPS |
|
|
Object Detection (F16)
|
100% |
1151
85.9 IPS |
|
|
Object Detection (I8)
|
97% |
514
38.3 IPS |
|
|
Face Detection (F32)
|
100% |
2388
28.4 IPS |
|
|
Face Detection (F16)
|
98% |
4823
57.4 IPS |
|
|
Face Detection (I8)
|
97% |
5055
60.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2472
19.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
21960
170.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
21569
167.3 IPS |
|
|
Style Transfer (F32)
|
100% |
5848
7.69 IPS |
|
|
Style Transfer (F16)
|
100% |
17888
23.5 IPS |
|
|
Style Transfer (I8)
|
100% |
17645
23.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
984
35.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5088
181.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5737
204.9 IPS |
|
|
Text Classification (F32)
|
100% |
233
335.3 IPS |
|
|
Text Classification (F16)
|
100% |
302
434.4 IPS |
|
|
Text Classification (I8)
|
96% |
309
443.5 IPS |
|
|
Machine Translation (F32)
|
100% |
199
3.66 IPS |
|
|
Machine Translation (F16)
|
100% |
202
3.72 IPS |
|
|
Machine Translation (I8)
|
99% |
208
3.83 IPS |
