iPhone 12 Pro Max
Geekbench ML Score
3893
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:40 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 12 Pro Max |
| Model ID | iPhone13,4 |
| Motherboard | D54pAP |
| CPU Information | |
|---|---|
| Name | Apple A14 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.99 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.52 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
338
63.3 IPS |
|
|
Image Classification (F16)
|
100% |
3794
710.0 IPS |
|
|
Image Classification (I8)
|
99% |
4763
891.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
578
9.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
3190
53.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
3407
56.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
5679
6.88 IPS |
|
|
Pose Estimation (F16)
|
100% |
54758
66.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
55865
67.7 IPS |
|
|
Object Detection (F32)
|
100% |
582
43.4 IPS |
|
|
Object Detection (F16)
|
100% |
3491
260.6 IPS |
|
|
Object Detection (I8)
|
97% |
649
48.5 IPS |
|
|
Face Detection (F32)
|
100% |
2794
33.2 IPS |
|
|
Face Detection (F16)
|
97% |
10450
124.2 IPS |
|
|
Face Detection (I8)
|
96% |
10552
125.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
5243
40.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
32447
251.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
36218
280.9 IPS |
|
|
Style Transfer (F32)
|
100% |
11253
14.8 IPS |
|
|
Style Transfer (F16)
|
100% |
96490
126.9 IPS |
|
|
Style Transfer (I8)
|
100% |
95914
126.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1642
58.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15175
542.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15045
537.3 IPS |
|
|
Text Classification (F32)
|
100% |
247
355.1 IPS |
|
|
Text Classification (F16)
|
100% |
897
1.29 KIPS |
|
|
Text Classification (I8)
|
96% |
325
467.5 IPS |
|
|
Machine Translation (F32)
|
100% |
326
6.01 IPS |
|
|
Machine Translation (F16)
|
100% |
1011
18.6 IPS |
|
|
Machine Translation (I8)
|
99% |
332
6.11 IPS |
