iPhone 15 Pro Max
Geekbench ML Score
5534
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:22 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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 | 7.44 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
879
164.5 IPS |
|
|
Image Classification (F16)
|
100% |
6269
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6986
1.31 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1324
22.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1815
30.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1792
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
14804
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
82737
100.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
83762
101.4 IPS |
|
|
Object Detection (F32)
|
100% |
982
73.3 IPS |
|
|
Object Detection (F16)
|
100% |
4422
330.1 IPS |
|
|
Object Detection (I8)
|
97% |
1062
79.3 IPS |
|
|
Face Detection (F32)
|
100% |
4456
53.0 IPS |
|
|
Face Detection (F16)
|
97% |
10606
126.1 IPS |
|
|
Face Detection (I8)
|
96% |
10604
126.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
11324
87.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
41975
325.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
46033
357.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29976
39.4 IPS |
|
|
Style Transfer (F16)
|
100% |
115449
151.9 IPS |
|
|
Style Transfer (I8)
|
100% |
122000
160.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4069
145.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18311
654.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17858
637.8 IPS |
|
|
Text Classification (F32)
|
100% |
466
669.3 IPS |
|
|
Text Classification (F16)
|
100% |
506
727.7 IPS |
|
|
Text Classification (I8)
|
96% |
311
446.9 IPS |
|
|
Machine Translation (F32)
|
100% |
633
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1586
29.2 IPS |
|
|
Machine Translation (I8)
|
99% |
551
10.1 IPS |
