iPhone 15 Pro Max
Geekbench AI Score
1528
Single Precision Score
2975
Half Precision Score
2500
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 14 2025 11:28 PM |
| Views | 1 |
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% |
615
114.3 IPS |
|
|
Image Classification (HP)
|
100% |
901
167.5 IPS |
|
|
Image Classification (Q)
|
96% |
588
109.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
528
8.56 IPS |
|
|
Image Segmentation (HP)
|
100% |
876
14.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
919
14.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2318
2.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
3808
4.44 IPS |
|
|
Pose Estimation (Q)
|
95% |
4226
4.95 IPS |
|
|
Object Detection (SP)
|
100% |
497
39.4 IPS |
|
|
Object Detection (HP)
|
97% |
1585
126.2 IPS |
|
|
Object Detection (Q)
|
94% |
1290
102.8 IPS |
|
|
Face Detection (SP)
|
100% |
1111
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
3544
42.1 IPS |
|
|
Face Detection (Q)
|
100% |
1166
13.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2232
17.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
6254
48.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
5043
39.4 IPS |
|
|
Style Transfer (SP)
|
100% |
12005
15.4 IPS |
|
|
Style Transfer (HP)
|
100% |
18567
23.9 IPS |
|
|
Style Transfer (Q)
|
96% |
15470
20.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2885
106.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3525
130.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2529
93.4 IPS |
|
|
Text Classification (SP)
|
100% |
1991
2.66 KIPS |
|
|
Text Classification (HP)
|
99% |
3315
4.43 KIPS |
|
|
Text Classification (Q)
|
93% |
3295
4.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
1087
18.7 IPS |
|
|
Machine Translation (HP)
|
98% |
2371
41.0 IPS |
|
|
Machine Translation (Q)
|
98% |
4275
73.9 IPS |
