iPhone 15 Pro Max
Geekbench AI Score
2917
Single Precision Score
5147
Half Precision Score
4166
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | August 18 2025 05:40 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1207
224.4 IPS |
|
|
Image Classification (HP)
|
100% |
2191
407.5 IPS |
|
|
Image Classification (Q)
|
96% |
1502
280.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1144
18.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1880
30.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2261
36.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6724
7.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
13130
15.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
11326
13.3 IPS |
|
|
Object Detection (SP)
|
100% |
1286
102.0 IPS |
|
|
Object Detection (HP)
|
97% |
2412
192.1 IPS |
|
|
Object Detection (Q)
|
94% |
1742
138.9 IPS |
|
|
Face Detection (SP)
|
100% |
2121
25.2 IPS |
|
|
Face Detection (HP)
|
100% |
4561
54.2 IPS |
|
|
Face Detection (Q)
|
100% |
2531
30.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5320
41.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
9573
74.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
6706
52.4 IPS |
|
|
Style Transfer (SP)
|
100% |
16677
21.4 IPS |
|
|
Style Transfer (HP)
|
100% |
25718
33.1 IPS |
|
|
Style Transfer (Q)
|
96% |
21148
27.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3847
142.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4485
165.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3276
121.0 IPS |
|
|
Text Classification (SP)
|
100% |
2544
3.40 KIPS |
|
|
Text Classification (HP)
|
99% |
4407
5.88 KIPS |
|
|
Text Classification (Q)
|
93% |
4364
5.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
2030
35.0 IPS |
|
|
Machine Translation (HP)
|
98% |
4508
77.9 IPS |
|
|
Machine Translation (Q)
|
98% |
4580
79.1 IPS |
