iPhone 15 Pro Max
Geekbench AI Score
3861
Single Precision Score
6717
Half Precision Score
5477
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | Odai |
| Upload Date | September 14 2024 12:07 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1694
315.0 IPS |
|
|
Image Classification (HP)
|
100% |
2926
544.1 IPS |
|
|
Image Classification (Q)
|
96% |
2013
375.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1602
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2353
38.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3039
49.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7627
8.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
15788
18.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
13708
16.1 IPS |
|
|
Object Detection (SP)
|
100% |
1728
137.1 IPS |
|
|
Object Detection (HP)
|
97% |
3277
260.9 IPS |
|
|
Object Detection (Q)
|
94% |
2302
183.5 IPS |
|
|
Face Detection (SP)
|
100% |
3146
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
6481
77.0 IPS |
|
|
Face Detection (Q)
|
100% |
3716
44.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6867
52.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
13118
101.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
9030
70.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20483
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
31977
41.1 IPS |
|
|
Style Transfer (Q)
|
96% |
26593
34.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4739
175.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5816
214.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4353
160.7 IPS |
|
|
Text Classification (SP)
|
100% |
3172
4.23 KIPS |
|
|
Text Classification (HP)
|
100% |
5585
7.45 KIPS |
|
|
Text Classification (Q)
|
93% |
5418
7.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3095
53.3 IPS |
|
|
Machine Translation (HP)
|
98% |
5946
102.7 IPS |
|
|
Machine Translation (Q)
|
98% |
5983
103.4 IPS |
