iPhone 15 Pro Max
Geekbench AI Score
3793
Single Precision Score
24497
Half Precision Score
34142
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 26 2025 07:20 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
1543
287.0 IPS |
|
|
Image Classification (HP)
|
100% |
10719
1.99 KIPS |
|
|
Image Classification (Q)
|
97% |
13207
2.46 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1535
24.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
16376
265.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21229
344.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7490
8.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
104285
121.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
199171
233.4 IPS |
|
|
Object Detection (SP)
|
100% |
1673
132.7 IPS |
|
|
Object Detection (HP)
|
100% |
11477
910.4 IPS |
|
|
Object Detection (Q)
|
91% |
15866
1.27 KIPS |
|
|
Face Detection (SP)
|
100% |
3017
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
34321
407.8 IPS |
|
|
Face Detection (Q)
|
100% |
46717
555.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6785
52.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
70359
542.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
120261
940.3 IPS |
|
|
Style Transfer (SP)
|
100% |
21074
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
197684
254.1 IPS |
|
|
Style Transfer (Q)
|
96% |
232758
300.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4646
171.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26418
975.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
53419
1.97 KIPS |
|
|
Text Classification (SP)
|
100% |
3230
4.31 KIPS |
|
|
Text Classification (HP)
|
99% |
5520
7.37 KIPS |
|
|
Text Classification (Q)
|
93% |
5401
7.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
3211
55.3 IPS |
|
|
Machine Translation (HP)
|
100% |
5322
91.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6439
111.3 IPS |
