iPhone 15 Pro Max
Geekbench AI Score
2653
Single Precision Score
13938
Half Precision Score
17830
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | wudi890 |
| Upload Date | October 01 2024 08:01 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.4 |
| 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 |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1375
255.8 IPS |
|
|
Image Classification (HP)
|
100% |
6127
1.14 KIPS |
|
|
Image Classification (Q)
|
97% |
7528
1.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
803
13.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5192
84.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
9956
161.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7118
8.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
87161
101.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
151017
177.0 IPS |
|
|
Object Detection (SP)
|
100% |
1459
115.7 IPS |
|
|
Object Detection (HP)
|
100% |
8144
646.0 IPS |
|
|
Object Detection (Q)
|
93% |
9884
788.7 IPS |
|
|
Face Detection (SP)
|
100% |
2162
25.7 IPS |
|
|
Face Detection (HP)
|
100% |
11072
131.6 IPS |
|
|
Face Detection (Q)
|
100% |
13196
156.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4547
35.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
42977
331.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
59165
462.6 IPS |
|
|
Style Transfer (SP)
|
100% |
12005
15.4 IPS |
|
|
Style Transfer (HP)
|
100% |
127632
164.1 IPS |
|
|
Style Transfer (Q)
|
96% |
137260
177.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3813
140.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18245
673.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
26013
960.5 IPS |
|
|
Text Classification (SP)
|
100% |
1769
2.36 KIPS |
|
|
Text Classification (HP)
|
71% |
4407
6.34 KIPS |
|
|
Text Classification (Q)
|
69% |
4154
6.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
1897
32.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2510
43.2 IPS |
|
|
Machine Translation (Q)
|
98% |
2507
43.3 IPS |
