iPhone 15 Pro Max
Geekbench AI Score
3850
Single Precision Score
26665
Half Precision Score
36578
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 03:36 PM |
| Views | 1 |
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% |
1584
294.5 IPS |
|
|
Image Classification (HP)
|
100% |
10987
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
15543
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1563
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
16339
264.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20949
339.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7753
9.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
107066
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
206814
242.4 IPS |
|
|
Object Detection (SP)
|
100% |
1683
133.5 IPS |
|
|
Object Detection (HP)
|
100% |
13973
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18239
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
3086
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
33895
402.7 IPS |
|
|
Face Detection (Q)
|
100% |
46291
550.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6964
53.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78314
603.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
123730
967.4 IPS |
|
|
Style Transfer (SP)
|
100% |
21416
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
205601
264.3 IPS |
|
|
Style Transfer (Q)
|
96% |
249864
322.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4737
174.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35035
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
61491
2.27 KIPS |
|
|
Text Classification (SP)
|
100% |
3201
4.27 KIPS |
|
|
Text Classification (HP)
|
99% |
5492
7.33 KIPS |
|
|
Text Classification (Q)
|
93% |
5494
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3181
54.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6445
111.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7222
124.8 IPS |
