iPhone 15 Pro Max
Geekbench AI Score
3683
Single Precision Score
25371
Half Precision Score
34856
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 07 2025 07:15 PM |
| Views | 1 |
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% |
1541
286.7 IPS |
|
|
Image Classification (HP)
|
100% |
11393
2.12 KIPS |
|
|
Image Classification (Q)
|
97% |
13995
2.61 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1513
24.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
16399
265.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
21299
345.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
6880
8.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
101718
118.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
200899
235.5 IPS |
|
|
Object Detection (SP)
|
100% |
1631
129.4 IPS |
|
|
Object Detection (HP)
|
100% |
12390
982.7 IPS |
|
|
Object Detection (Q)
|
91% |
16373
1.31 KIPS |
|
|
Face Detection (SP)
|
100% |
2990
35.5 IPS |
|
|
Face Detection (HP)
|
100% |
34039
404.5 IPS |
|
|
Face Detection (Q)
|
100% |
51531
612.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6521
50.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
71712
552.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
110327
862.6 IPS |
|
|
Style Transfer (SP)
|
100% |
19989
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
200815
258.2 IPS |
|
|
Style Transfer (Q)
|
96% |
242868
313.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4440
164.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29219
1.08 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56225
2.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3227
4.31 KIPS |
|
|
Text Classification (HP)
|
99% |
5567
7.43 KIPS |
|
|
Text Classification (Q)
|
93% |
5470
7.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
3147
54.2 IPS |
|
|
Machine Translation (HP)
|
100% |
5886
101.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6358
109.9 IPS |
