iPhone 15 Pro Max
Geekbench AI Score
3911
Single Precision Score
6816
Half Precision Score
5565
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | mvodya |
| Upload Date | February 03 2025 08:01 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1697
315.6 IPS |
|
|
Image Classification (HP)
|
100% |
2915
542.0 IPS |
|
|
Image Classification (Q)
|
96% |
2018
376.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1618
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2465
40.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3080
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7975
9.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
16219
18.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
14197
16.6 IPS |
|
|
Object Detection (SP)
|
100% |
1760
139.6 IPS |
|
|
Object Detection (HP)
|
97% |
3329
265.1 IPS |
|
|
Object Detection (Q)
|
94% |
2345
186.9 IPS |
|
|
Face Detection (SP)
|
100% |
3129
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
6720
79.9 IPS |
|
|
Face Detection (Q)
|
100% |
3826
45.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6879
53.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
13363
103.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
9148
71.5 IPS |
|
|
Style Transfer (SP)
|
100% |
20867
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
32269
41.5 IPS |
|
|
Style Transfer (Q)
|
96% |
27274
35.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4861
179.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5765
212.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4347
160.5 IPS |
|
|
Text Classification (SP)
|
100% |
3199
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5538
7.39 KIPS |
|
|
Text Classification (Q)
|
93% |
5523
7.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3112
53.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6038
104.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6010
103.9 IPS |
