iPhone 15 Pro Max
Geekbench AI Score
3813
Single Precision Score
26570
Half Precision Score
36486
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 09:11 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% |
1578
293.5 IPS |
|
|
Image Classification (HP)
|
100% |
10786
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15330
2.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1548
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16377
265.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21201
343.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7528
8.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
106922
124.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
205355
240.7 IPS |
|
|
Object Detection (SP)
|
100% |
1666
132.2 IPS |
|
|
Object Detection (HP)
|
100% |
13859
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
17779
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3073
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
33688
400.3 IPS |
|
|
Face Detection (Q)
|
100% |
50375
598.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6891
53.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78298
603.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
124558
973.9 IPS |
|
|
Style Transfer (SP)
|
100% |
21075
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
209074
268.8 IPS |
|
|
Style Transfer (Q)
|
96% |
251367
324.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4701
173.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34388
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58250
2.15 KIPS |
|
|
Text Classification (SP)
|
100% |
3244
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5426
7.24 KIPS |
|
|
Text Classification (Q)
|
93% |
5431
7.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3120
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6511
112.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7062
122.0 IPS |
