iPhone 15 Pro Max
Geekbench AI Score
3867
Single Precision Score
26592
Half Precision Score
36387
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 06 2025 06:30 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1645
305.9 IPS |
|
|
Image Classification (HP)
|
100% |
10799
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
14860
2.77 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1586
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16381
265.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21174
343.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7854
9.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
106307
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
204834
240.1 IPS |
|
|
Object Detection (SP)
|
100% |
1752
139.0 IPS |
|
|
Object Detection (HP)
|
100% |
13851
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
17798
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3081
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
34321
407.8 IPS |
|
|
Face Detection (Q)
|
100% |
49570
589.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6915
53.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78336
603.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
125228
979.1 IPS |
|
|
Style Transfer (SP)
|
100% |
20703
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
207070
266.2 IPS |
|
|
Style Transfer (Q)
|
96% |
247880
319.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4569
168.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34213
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58031
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3276
4.37 KIPS |
|
|
Text Classification (HP)
|
99% |
5563
7.43 KIPS |
|
|
Text Classification (Q)
|
93% |
5543
7.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
3156
54.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6407
110.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7168
123.9 IPS |
