iPhone 15 Pro Max
Geekbench AI Score
3824
Single Precision Score
26757
Half Precision Score
36562
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 22 2025 06:34 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| 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% |
1559
289.9 IPS |
|
|
Image Classification (HP)
|
100% |
10784
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15567
2.91 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1544
25.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16323
264.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21017
340.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7740
9.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
106741
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
206266
241.8 IPS |
|
|
Object Detection (SP)
|
100% |
1657
131.5 IPS |
|
|
Object Detection (HP)
|
100% |
13686
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
17822
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3095
36.8 IPS |
|
|
Face Detection (HP)
|
100% |
36258
430.8 IPS |
|
|
Face Detection (Q)
|
100% |
51490
611.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6898
53.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78022
601.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
122734
959.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21141
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
208027
267.4 IPS |
|
|
Style Transfer (Q)
|
96% |
250234
322.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4784
176.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34773
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57880
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3219
4.30 KIPS |
|
|
Text Classification (HP)
|
99% |
5585
7.45 KIPS |
|
|
Text Classification (Q)
|
93% |
5562
7.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
3117
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6402
110.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6972
120.5 IPS |
