iPhone 14 Pro Max
Geekbench ML Score
5048
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 19 2024 02:28 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
1091
204.1 IPS |
|
|
Image Classification (F16)
|
100% |
5347
1.00 KIPS |
|
|
Image Classification (I8)
|
99% |
5647
1.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1135
19.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1626
27.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1588
26.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
11186
13.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
76691
92.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
70078
84.9 IPS |
|
|
Object Detection (F32)
|
100% |
1401
104.6 IPS |
|
|
Object Detection (F16)
|
100% |
4208
314.1 IPS |
|
|
Object Detection (I8)
|
97% |
1421
106.1 IPS |
|
|
Face Detection (F32)
|
100% |
4940
58.7 IPS |
|
|
Face Detection (F16)
|
97% |
10130
120.5 IPS |
|
|
Face Detection (I8)
|
96% |
10463
124.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
8833
68.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
33134
257.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
43965
340.9 IPS |
|
|
Style Transfer (F32)
|
100% |
21051
27.7 IPS |
|
|
Style Transfer (F16)
|
100% |
116035
152.6 IPS |
|
|
Style Transfer (I8)
|
100% |
113237
149.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4226
150.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16301
582.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16573
591.9 IPS |
|
|
Text Classification (F32)
|
100% |
356
511.5 IPS |
|
|
Text Classification (F16)
|
100% |
357
512.6 IPS |
|
|
Text Classification (I8)
|
96% |
247
355.6 IPS |
|
|
Machine Translation (F32)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1091
20.1 IPS |
|
|
Machine Translation (I8)
|
99% |
587
10.8 IPS |
