iPhone 15 Pro Max
Geekbench AI Score
3793
Single Precision Score
26862
Half Precision Score
36562
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 26 2025 05:32 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1575
292.9 IPS |
|
|
Image Classification (HP)
|
100% |
11113
2.07 KIPS |
|
|
Image Classification (Q)
|
97% |
14519
2.71 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1546
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16678
270.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21232
344.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7683
8.96 IPS |
|
|
Pose Estimation (HP)
|
100% |
107137
125.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
206255
241.7 IPS |
|
|
Object Detection (SP)
|
100% |
1667
132.2 IPS |
|
|
Object Detection (HP)
|
100% |
13935
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18247
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
3030
36.0 IPS |
|
|
Face Detection (HP)
|
100% |
34488
409.8 IPS |
|
|
Face Detection (Q)
|
100% |
51209
608.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6764
52.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78403
604.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
129771
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21067
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
209002
268.7 IPS |
|
|
Style Transfer (Q)
|
96% |
250263
323.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4637
171.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35588
1.31 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56479
2.09 KIPS |
|
|
Text Classification (SP)
|
100% |
3195
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5512
7.36 KIPS |
|
|
Text Classification (Q)
|
93% |
5483
7.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
3090
53.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6377
109.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7145
123.5 IPS |
