iPhone 13 Pro Max
Geekbench ML Score
5969
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 18 2024 01:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 13 Pro Max |
| Model ID | iPhone14,3 |
| Motherboard | D64AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 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 | 5.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1270
237.6 IPS |
|
|
Image Classification (F16)
|
100% |
4769
892.4 IPS |
|
|
Image Classification (I8)
|
99% |
5044
943.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1147
19.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1509
25.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1498
25.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
10977
13.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
75790
91.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
78026
94.5 IPS |
|
|
Object Detection (F32)
|
100% |
1484
110.8 IPS |
|
|
Object Detection (F16)
|
100% |
4056
302.8 IPS |
|
|
Object Detection (I8)
|
97% |
1502
112.1 IPS |
|
|
Face Detection (F32)
|
100% |
4440
52.8 IPS |
|
|
Face Detection (F16)
|
97% |
11220
133.4 IPS |
|
|
Face Detection (I8)
|
96% |
11160
132.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
9155
71.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
36299
281.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
39342
305.1 IPS |
|
|
Style Transfer (F32)
|
100% |
18645
24.5 IPS |
|
|
Style Transfer (F16)
|
100% |
95190
125.2 IPS |
|
|
Style Transfer (I8)
|
100% |
93000
122.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4176
149.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15734
561.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14953
534.0 IPS |
|
|
Text Classification (F32)
|
100% |
2207
3.17 KIPS |
|
|
Text Classification (F16)
|
100% |
2017
2.90 KIPS |
|
|
Text Classification (I8)
|
96% |
2409
3.46 KIPS |
|
|
Machine Translation (F32)
|
100% |
557
10.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1079
19.9 IPS |
|
|
Machine Translation (I8)
|
99% |
536
9.87 IPS |
