iPhone 15 Pro Max
Geekbench AI Score
3849
Single Precision Score
26599
Half Precision Score
36243
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 27 2025 03:57 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% |
1581
294.1 IPS |
|
|
Image Classification (HP)
|
100% |
10914
2.03 KIPS |
|
|
Image Classification (Q)
|
97% |
15481
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1617
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16633
269.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21559
349.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7771
9.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
107142
125.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
206700
242.3 IPS |
|
|
Object Detection (SP)
|
100% |
1681
133.3 IPS |
|
|
Object Detection (HP)
|
100% |
13198
1.05 KIPS |
|
|
Object Detection (Q)
|
91% |
17447
1.39 KIPS |
|
|
Face Detection (SP)
|
100% |
3084
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
36384
432.3 IPS |
|
|
Face Detection (Q)
|
100% |
50205
596.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6936
53.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78341
603.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
125116
978.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21310
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
206376
265.3 IPS |
|
|
Style Transfer (Q)
|
96% |
247019
318.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4732
174.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34324
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58332
2.15 KIPS |
|
|
Text Classification (SP)
|
100% |
3195
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5448
7.27 KIPS |
|
|
Text Classification (Q)
|
93% |
5385
7.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
3105
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6280
108.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6667
115.2 IPS |
