iPhone 15 Pro Max
Geekbench AI Score
3779
Single Precision Score
26751
Half Precision Score
35628
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 17 2025 04:29 PM |
| Views | 2 |
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% |
1572
292.3 IPS |
|
|
Image Classification (HP)
|
100% |
11621
2.16 KIPS |
|
|
Image Classification (Q)
|
97% |
14913
2.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1560
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
16427
266.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
21369
346.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7311
8.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
105960
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
203536
238.6 IPS |
|
|
Object Detection (SP)
|
100% |
1667
132.3 IPS |
|
|
Object Detection (HP)
|
100% |
13605
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
17490
1.40 KIPS |
|
|
Face Detection (SP)
|
100% |
3046
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
36667
435.7 IPS |
|
|
Face Detection (Q)
|
100% |
49645
589.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6784
52.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78259
602.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
123351
964.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20941
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
204329
262.7 IPS |
|
|
Style Transfer (Q)
|
96% |
241829
312.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4616
170.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34229
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54334
2.01 KIPS |
|
|
Text Classification (SP)
|
100% |
3207
4.28 KIPS |
|
|
Text Classification (HP)
|
99% |
5518
7.37 KIPS |
|
|
Text Classification (Q)
|
93% |
5430
7.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3109
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6159
106.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6649
114.9 IPS |
