iPhone 15 Pro Max
Geekbench AI Score
5029
Single Precision Score
5954
Half Precision Score
5193
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 04:20 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A17 Pro |
| 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 |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1968
366.1 IPS |
|
|
Image Classification (HP)
|
100% |
2061
383.3 IPS |
|
|
Image Classification (Q)
|
97% |
1803
336.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2990
48.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
3964
64.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
4008
65.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
15096
17.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
15910
18.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
14739
17.3 IPS |
|
|
Object Detection (SP)
|
100% |
2751
218.2 IPS |
|
|
Object Detection (HP)
|
100% |
2786
221.0 IPS |
|
|
Object Detection (Q)
|
91% |
2205
176.2 IPS |
|
|
Face Detection (SP)
|
100% |
6409
76.1 IPS |
|
|
Face Detection (HP)
|
100% |
8881
105.5 IPS |
|
|
Face Detection (Q)
|
100% |
6188
73.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
11633
89.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
12886
99.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
10428
81.5 IPS |
|
|
Style Transfer (SP)
|
100% |
29880
38.4 IPS |
|
|
Style Transfer (HP)
|
100% |
35759
46.0 IPS |
|
|
Style Transfer (Q)
|
96% |
32077
41.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6526
241.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7003
258.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5267
194.5 IPS |
|
|
Text Classification (SP)
|
100% |
3196
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5704
7.61 KIPS |
|
|
Text Classification (Q)
|
93% |
5704
7.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
912
15.7 IPS |
|
|
Machine Translation (HP)
|
100% |
947
16.3 IPS |
|
|
Machine Translation (Q)
|
98% |
978
16.9 IPS |
