iPhone 15 Pro Max
Geekbench AI Score
2078
Single Precision Score
3830
Half Precision Score
3119
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | December 10 2025 01:37 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
823
153.0 IPS |
|
|
Image Classification (HP)
|
100% |
1612
299.8 IPS |
|
|
Image Classification (Q)
|
96% |
1066
199.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
756
12.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1394
22.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
1669
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
3975
4.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
8860
10.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
7925
9.29 IPS |
|
|
Object Detection (SP)
|
100% |
858
68.0 IPS |
|
|
Object Detection (HP)
|
97% |
1821
145.0 IPS |
|
|
Object Detection (Q)
|
94% |
1295
103.2 IPS |
|
|
Face Detection (SP)
|
100% |
1806
21.5 IPS |
|
|
Face Detection (HP)
|
100% |
3559
42.3 IPS |
|
|
Face Detection (Q)
|
100% |
2004
23.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
3577
27.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
6719
51.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
4870
38.1 IPS |
|
|
Style Transfer (SP)
|
100% |
11216
14.4 IPS |
|
|
Style Transfer (HP)
|
100% |
17430
22.4 IPS |
|
|
Style Transfer (Q)
|
96% |
14760
19.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2697
99.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3219
118.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2408
88.9 IPS |
|
|
Text Classification (SP)
|
100% |
1920
2.56 KIPS |
|
|
Text Classification (HP)
|
99% |
3257
4.35 KIPS |
|
|
Text Classification (Q)
|
93% |
3234
4.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
1893
32.6 IPS |
|
|
Machine Translation (HP)
|
98% |
4297
74.2 IPS |
|
|
Machine Translation (Q)
|
98% |
4267
73.7 IPS |
