iPhone 15 Pro Max
Geekbench AI Score
3728
Single Precision Score
27012
Half Precision Score
36831
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 24 2025 03:38 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% |
1576
293.1 IPS |
|
|
Image Classification (HP)
|
100% |
11076
2.06 KIPS |
|
|
Image Classification (Q)
|
97% |
15403
2.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1533
24.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
16675
270.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
21558
349.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7354
8.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
106173
123.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
206355
241.9 IPS |
|
|
Object Detection (SP)
|
100% |
1623
128.7 IPS |
|
|
Object Detection (HP)
|
100% |
13958
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
17676
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
2948
35.0 IPS |
|
|
Face Detection (HP)
|
100% |
36535
434.1 IPS |
|
|
Face Detection (Q)
|
100% |
51216
608.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6627
51.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78423
604.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
126553
989.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20117
25.9 IPS |
|
|
Style Transfer (HP)
|
100% |
207998
267.4 IPS |
|
|
Style Transfer (Q)
|
96% |
248120
320.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4529
167.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34671
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57635
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3237
4.32 KIPS |
|
|
Text Classification (HP)
|
99% |
5637
7.52 KIPS |
|
|
Text Classification (Q)
|
93% |
5590
7.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
3122
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6489
111.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7321
126.5 IPS |
