iPhone 15 Pro Max
Geekbench AI Score
3722
Single Precision Score
20354
Half Precision Score
30548
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| Upload Date | February 07 2026 01:27 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2.1 |
| 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% |
1575
292.8 IPS |
|
|
Image Classification (HP)
|
100% |
7983
1.48 KIPS |
|
|
Image Classification (Q)
|
97% |
10805
2.02 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1528
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16455
266.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
21255
344.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6860
8.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
99964
116.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
180648
211.7 IPS |
|
|
Object Detection (SP)
|
100% |
1639
130.0 IPS |
|
|
Object Detection (HP)
|
100% |
8003
634.8 IPS |
|
|
Object Detection (Q)
|
91% |
15412
1.23 KIPS |
|
|
Face Detection (SP)
|
100% |
2981
35.4 IPS |
|
|
Face Detection (HP)
|
100% |
34603
411.2 IPS |
|
|
Face Detection (Q)
|
100% |
43688
519.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6584
50.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
66685
513.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
78153
611.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20763
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
177771
228.5 IPS |
|
|
Style Transfer (Q)
|
96% |
208581
269.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4580
169.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
20169
744.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
42987
1.59 KIPS |
|
|
Text Classification (SP)
|
100% |
3238
4.32 KIPS |
|
|
Text Classification (HP)
|
99% |
5542
7.40 KIPS |
|
|
Text Classification (Q)
|
93% |
5474
7.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
3122
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2533
43.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6605
114.1 IPS |
