iPhone 15 Pro Max
Geekbench ML Score
6095
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 07:30 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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% |
1698
317.7 IPS |
|
|
Image Classification (F16)
|
100% |
6250
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6897
1.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1396
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1722
28.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1759
29.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
14785
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
83641
101.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
86332
104.5 IPS |
|
|
Object Detection (F32)
|
100% |
1812
135.3 IPS |
|
|
Object Detection (F16)
|
100% |
3657
273.0 IPS |
|
|
Object Detection (I8)
|
97% |
1904
142.1 IPS |
|
|
Face Detection (F32)
|
100% |
6171
73.4 IPS |
|
|
Face Detection (F16)
|
97% |
10577
125.8 IPS |
|
|
Face Detection (I8)
|
96% |
10599
126.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
12331
95.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
37684
292.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
47994
372.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29175
38.4 IPS |
|
|
Style Transfer (F16)
|
100% |
121288
159.5 IPS |
|
|
Style Transfer (I8)
|
100% |
120012
157.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7140
255.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17672
631.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18511
661.1 IPS |
|
|
Text Classification (F32)
|
100% |
463
664.8 IPS |
|
|
Text Classification (F16)
|
100% |
504
724.0 IPS |
|
|
Text Classification (I8)
|
96% |
309
444.0 IPS |
|
|
Machine Translation (F32)
|
100% |
744
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1530
28.2 IPS |
|
|
Machine Translation (I8)
|
99% |
677
12.5 IPS |
