iPhone 15 Pro Max
Geekbench ML Score
7516
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 02:06 PM |
| Views | 240 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 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 | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1324
247.8 IPS |
|
|
Image Classification (F16)
|
100% |
6285
1.18 KIPS |
|
|
Image Classification (I8)
|
99% |
6749
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1429
23.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1809
30.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1812
30.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
14757
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
86832
105.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
88675
107.4 IPS |
|
|
Object Detection (F32)
|
100% |
1463
109.2 IPS |
|
|
Object Detection (F16)
|
100% |
3873
289.2 IPS |
|
|
Object Detection (I8)
|
97% |
2118
158.1 IPS |
|
|
Face Detection (F32)
|
100% |
5893
70.1 IPS |
|
|
Face Detection (F16)
|
97% |
12698
151.0 IPS |
|
|
Face Detection (I8)
|
96% |
12704
151.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12136
94.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
34871
270.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
34934
270.9 IPS |
|
|
Style Transfer (F32)
|
100% |
29253
38.5 IPS |
|
|
Style Transfer (F16)
|
100% |
115354
151.7 IPS |
|
|
Style Transfer (I8)
|
100% |
119552
157.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7082
252.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17655
630.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17084
610.1 IPS |
|
|
Text Classification (F32)
|
100% |
2896
4.16 KIPS |
|
|
Text Classification (F16)
|
100% |
4880
7.01 KIPS |
|
|
Text Classification (I8)
|
96% |
4937
7.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
627
11.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1572
28.9 IPS |
|
|
Machine Translation (I8)
|
99% |
639
11.8 IPS |
