iPhone 15 Pro Max
Geekbench AI Score
3952
Single Precision Score
26471
Half Precision Score
34886
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | September 04 2025 12:03 PM |
| Views | 2 |
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% |
1655
307.7 IPS |
|
|
Image Classification (HP)
|
100% |
10943
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
13830
2.58 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1601
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
16673
270.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
21225
344.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8216
9.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
105998
123.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
201593
236.3 IPS |
|
|
Object Detection (SP)
|
100% |
1764
139.9 IPS |
|
|
Object Detection (HP)
|
100% |
13692
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
17289
1.38 KIPS |
|
|
Face Detection (SP)
|
100% |
3147
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
33904
402.8 IPS |
|
|
Face Detection (Q)
|
100% |
45760
543.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7104
54.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78387
603.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
122474
957.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21084
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
202186
259.9 IPS |
|
|
Style Transfer (Q)
|
96% |
244745
315.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4935
182.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35075
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
53280
1.97 KIPS |
|
|
Text Classification (SP)
|
100% |
3257
4.35 KIPS |
|
|
Text Classification (HP)
|
99% |
5605
7.48 KIPS |
|
|
Text Classification (Q)
|
93% |
5500
7.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
3199
55.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6041
104.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6494
112.2 IPS |
