iPhone 14 Pro Max
Geekbench ML Score
6434
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:35 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1169
218.8 IPS |
|
|
Image Classification (F16)
|
100% |
5699
1.07 KIPS |
|
|
Image Classification (I8)
|
99% |
5968
1.12 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1074
17.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1548
25.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1565
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
11480
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
82377
99.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
79569
96.4 IPS |
|
|
Object Detection (F32)
|
100% |
1411
105.4 IPS |
|
|
Object Detection (F16)
|
100% |
4177
311.8 IPS |
|
|
Object Detection (I8)
|
97% |
1589
118.6 IPS |
|
|
Face Detection (F32)
|
100% |
4854
57.7 IPS |
|
|
Face Detection (F16)
|
97% |
11614
138.1 IPS |
|
|
Face Detection (I8)
|
96% |
11746
139.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
8908
69.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
36881
286.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
40546
314.4 IPS |
|
|
Style Transfer (F32)
|
100% |
21121
27.8 IPS |
|
|
Style Transfer (F16)
|
100% |
111573
146.8 IPS |
|
|
Style Transfer (I8)
|
100% |
107222
141.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4361
155.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17211
614.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17700
632.1 IPS |
|
|
Text Classification (F32)
|
100% |
2476
3.56 KIPS |
|
|
Text Classification (F16)
|
100% |
3251
4.67 KIPS |
|
|
Text Classification (I8)
|
96% |
3335
4.79 KIPS |
|
|
Machine Translation (F32)
|
100% |
548
10.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1018
18.7 IPS |
|
|
Machine Translation (I8)
|
99% |
556
10.2 IPS |
