iPhone 14 Pro Max
Geekbench ML Score
2709
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | evenwebb |
| Upload Date | February 23 2024 12:27 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3.1 |
| 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 | 5.49 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1217
227.7 IPS |
|
|
Image Classification (F16)
|
100% |
1179
220.7 IPS |
|
|
Image Classification (I8)
|
99% |
1297
242.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1141
19.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1197
20.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1191
19.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
11150
13.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
12034
14.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
11939
14.5 IPS |
|
|
Object Detection (F32)
|
100% |
1418
105.9 IPS |
|
|
Object Detection (F16)
|
100% |
1370
102.3 IPS |
|
|
Object Detection (I8)
|
97% |
1416
105.7 IPS |
|
|
Face Detection (F32)
|
100% |
5174
61.5 IPS |
|
|
Face Detection (F16)
|
97% |
5490
65.3 IPS |
|
|
Face Detection (I8)
|
96% |
5470
65.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
8653
67.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
9409
73.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
8583
66.6 IPS |
|
|
Style Transfer (F32)
|
100% |
20101
26.4 IPS |
|
|
Style Transfer (F16)
|
100% |
22365
29.4 IPS |
|
|
Style Transfer (I8)
|
100% |
23309
30.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4186
149.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4544
162.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4262
152.2 IPS |
|
|
Text Classification (F32)
|
100% |
374
537.4 IPS |
|
|
Text Classification (F16)
|
100% |
380
545.6 IPS |
|
|
Text Classification (I8)
|
96% |
256
367.7 IPS |
|
|
Machine Translation (F32)
|
100% |
590
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
638
11.7 IPS |
|
|
Machine Translation (I8)
|
99% |
573
10.5 IPS |
