iPhone 15 Pro Max
Geekbench AI Score
3794
Single Precision Score
24222
Half Precision Score
33428
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 12:17 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1482
275.5 IPS |
|
|
Image Classification (HP)
|
100% |
10188
1.89 KIPS |
|
|
Image Classification (Q)
|
97% |
12130
2.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1544
25.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16659
270.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
21344
346.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7321
8.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
104781
122.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
199427
233.7 IPS |
|
|
Object Detection (SP)
|
100% |
1675
132.9 IPS |
|
|
Object Detection (HP)
|
100% |
12512
992.4 IPS |
|
|
Object Detection (Q)
|
91% |
16818
1.34 KIPS |
|
|
Face Detection (SP)
|
100% |
3072
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
33945
403.3 IPS |
|
|
Face Detection (Q)
|
100% |
50934
605.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6879
53.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
62768
483.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
113472
887.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21338
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
190662
245.1 IPS |
|
|
Style Transfer (Q)
|
96% |
226167
291.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4716
174.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25262
932.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
44345
1.64 KIPS |
|
|
Text Classification (SP)
|
100% |
3301
4.41 KIPS |
|
|
Text Classification (HP)
|
99% |
5427
7.24 KIPS |
|
|
Text Classification (Q)
|
93% |
5435
7.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3139
54.1 IPS |
|
|
Machine Translation (HP)
|
100% |
5610
96.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6370
110.1 IPS |
