iPhone 15 Pro Max
Geekbench AI Score
3693
Single Precision Score
27138
Half Precision Score
36502
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| Upload Date | February 12 2026 01:05 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| 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% |
1473
274.0 IPS |
|
|
Image Classification (HP)
|
100% |
11792
2.19 KIPS |
|
|
Image Classification (Q)
|
97% |
16526
3.08 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1583
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16573
268.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
21131
342.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6981
8.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
102931
120.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
205993
241.4 IPS |
|
|
Object Detection (SP)
|
100% |
1637
129.9 IPS |
|
|
Object Detection (HP)
|
100% |
13668
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
17627
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
2941
35.0 IPS |
|
|
Face Detection (HP)
|
100% |
37290
443.1 IPS |
|
|
Face Detection (Q)
|
100% |
47086
559.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6694
51.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78569
605.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
125092
978.0 IPS |
|
|
Style Transfer (SP)
|
100% |
19677
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
209723
269.6 IPS |
|
|
Style Transfer (Q)
|
96% |
246510
318.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4609
170.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35786
1.32 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56286
2.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3186
4.25 KIPS |
|
|
Text Classification (HP)
|
99% |
5556
7.42 KIPS |
|
|
Text Classification (Q)
|
93% |
5578
7.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3120
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6451
111.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7265
125.5 IPS |
