iPhone 14 Pro Max
Geekbench ML Score
5635
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 01 2024 08:59 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 14 Pro Max |
| Model ID | iPhone15,3 |
| Motherboard | D74AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 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 | 5.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1845
345.2 IPS |
|
|
Image Classification (F16)
|
100% |
5558
1.04 KIPS |
|
|
Image Classification (I8)
|
99% |
5672
1.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1137
19.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1580
26.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1616
27.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
11147
13.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
79373
96.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
81626
98.8 IPS |
|
|
Object Detection (F32)
|
100% |
1839
137.3 IPS |
|
|
Object Detection (F16)
|
100% |
4642
346.5 IPS |
|
|
Object Detection (I8)
|
97% |
1426
106.5 IPS |
|
|
Face Detection (F32)
|
100% |
5167
61.4 IPS |
|
|
Face Detection (F16)
|
97% |
10171
120.9 IPS |
|
|
Face Detection (I8)
|
96% |
9380
111.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
7923
61.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
44429
344.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
43740
339.2 IPS |
|
|
Style Transfer (F32)
|
100% |
20587
27.1 IPS |
|
|
Style Transfer (F16)
|
100% |
112677
148.2 IPS |
|
|
Style Transfer (I8)
|
100% |
113528
149.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4298
153.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16147
576.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16287
581.7 IPS |
|
|
Text Classification (F32)
|
100% |
524
752.6 IPS |
|
|
Text Classification (F16)
|
100% |
672
966.3 IPS |
|
|
Text Classification (I8)
|
96% |
418
600.4 IPS |
|
|
Machine Translation (F32)
|
100% |
654
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1784
32.8 IPS |
|
|
Machine Translation (I8)
|
99% |
586
10.8 IPS |
