iPhone 15 Pro Max
Geekbench AI Score
3840
Single Precision Score
24761
Half Precision Score
34436
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 13 2025 02:58 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% |
1568
291.7 IPS |
|
|
Image Classification (HP)
|
100% |
10347
1.92 KIPS |
|
|
Image Classification (Q)
|
97% |
13941
2.60 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1526
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16359
265.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
21539
349.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7620
8.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
102650
119.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
196314
230.1 IPS |
|
|
Object Detection (SP)
|
100% |
1735
137.6 IPS |
|
|
Object Detection (HP)
|
100% |
11412
905.2 IPS |
|
|
Object Detection (Q)
|
91% |
15999
1.28 KIPS |
|
|
Face Detection (SP)
|
100% |
3064
36.4 IPS |
|
|
Face Detection (HP)
|
100% |
36503
433.7 IPS |
|
|
Face Detection (Q)
|
100% |
51014
606.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6930
53.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
69790
537.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
109388
855.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21089
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
196564
252.7 IPS |
|
|
Style Transfer (Q)
|
96% |
233733
301.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4785
176.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27220
1.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55106
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3261
4.35 KIPS |
|
|
Text Classification (HP)
|
99% |
5436
7.26 KIPS |
|
|
Text Classification (Q)
|
93% |
5410
7.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3161
54.4 IPS |
|
|
Machine Translation (HP)
|
100% |
5898
101.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6396
110.5 IPS |
