iPhone 15 Pro Max
Geekbench AI Score
3851
Single Precision Score
6823
Half Precision Score
5570
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | kngo |
| Upload Date | January 25 2025 12:48 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| 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 |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1613
300.0 IPS |
|
|
Image Classification (HP)
|
100% |
2965
551.3 IPS |
|
|
Image Classification (Q)
|
96% |
2060
384.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1622
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2562
41.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
3084
50.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7606
8.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
15538
18.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
13594
15.9 IPS |
|
|
Object Detection (SP)
|
100% |
1731
137.3 IPS |
|
|
Object Detection (HP)
|
97% |
3300
262.7 IPS |
|
|
Object Detection (Q)
|
94% |
2321
185.0 IPS |
|
|
Face Detection (SP)
|
100% |
3132
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
6692
79.5 IPS |
|
|
Face Detection (Q)
|
100% |
3791
45.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6899
53.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
13291
102.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
9082
71.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20426
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
32100
41.3 IPS |
|
|
Style Transfer (Q)
|
96% |
27165
35.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4758
175.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5966
220.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4394
162.3 IPS |
|
|
Text Classification (SP)
|
100% |
3208
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
5519
7.37 KIPS |
|
|
Text Classification (Q)
|
93% |
5716
7.67 KIPS |
|
|
Machine Translation (SP)
|
100% |
3092
53.3 IPS |
|
|
Machine Translation (HP)
|
98% |
5976
103.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6113
105.6 IPS |
