iPhone 15 Pro Max
Geekbench AI Score
3734
Single Precision Score
22474
Half Precision Score
32241
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 29 2025 05:43 AM |
| Views | 4 |
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% |
1569
291.8 IPS |
|
|
Image Classification (HP)
|
100% |
8279
1.54 KIPS |
|
|
Image Classification (Q)
|
97% |
11713
2.19 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1518
24.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
16684
270.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21153
342.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7154
8.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
102409
119.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
196948
230.8 IPS |
|
|
Object Detection (SP)
|
100% |
1636
129.8 IPS |
|
|
Object Detection (HP)
|
100% |
11961
948.7 IPS |
|
|
Object Detection (Q)
|
91% |
16678
1.33 KIPS |
|
|
Face Detection (SP)
|
100% |
2972
35.3 IPS |
|
|
Face Detection (HP)
|
100% |
34566
410.7 IPS |
|
|
Face Detection (Q)
|
100% |
47869
568.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6629
51.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
59589
459.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
86390
675.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20795
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
185467
238.4 IPS |
|
|
Style Transfer (Q)
|
96% |
220530
284.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4587
169.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
22347
825.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
48897
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
3226
4.31 KIPS |
|
|
Text Classification (HP)
|
99% |
5403
7.21 KIPS |
|
|
Text Classification (Q)
|
93% |
5390
7.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
3124
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
4212
72.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6205
107.2 IPS |
