iPhone 11 Pro Max
Geekbench ML Score
1876
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 20 2025 09:22 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.0.2 |
| 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% |
310
58.1 IPS |
|
|
Image Classification (F16)
|
100% |
2725
509.9 IPS |
|
|
Image Classification (I8)
|
99% |
2744
513.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
290
4.84 IPS |
|
|
Image Segmentation (F16)
|
100% |
493
8.24 IPS |
|
|
Image Segmentation (I8)
|
100% |
489
8.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
2273
2.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
25919
31.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
26448
32.0 IPS |
|
|
Object Detection (F32)
|
100% |
581
43.4 IPS |
|
|
Object Detection (F16)
|
100% |
977
73.0 IPS |
|
|
Object Detection (I8)
|
97% |
508
37.9 IPS |
|
|
Face Detection (F32)
|
100% |
2439
29.0 IPS |
|
|
Face Detection (F16)
|
97% |
4378
52.1 IPS |
|
|
Face Detection (I8)
|
96% |
4307
51.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2680
20.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
22742
176.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
24573
190.6 IPS |
|
|
Style Transfer (F32)
|
24% |
6065
7.98 IPS |
|
|
Style Transfer (F16)
|
100% |
17535
23.1 IPS |
|
|
Style Transfer (I8)
|
100% |
17614
23.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1406
50.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4992
178.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5139
183.5 IPS |
|
|
Text Classification (F32)
|
100% |
247
355.2 IPS |
|
|
Text Classification (F16)
|
100% |
326
468.3 IPS |
|
|
Text Classification (I8)
|
96% |
322
463.4 IPS |
|
|
Machine Translation (F32)
|
100% |
301
5.54 IPS |
|
|
Machine Translation (F16)
|
100% |
208
3.82 IPS |
|
|
Machine Translation (I8)
|
99% |
290
5.33 IPS |
