iPhone 15 Pro Max
Geekbench AI Score
3980
Single Precision Score
24135
Half Precision Score
33571
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 14 2025 04:14 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1642
305.3 IPS |
|
|
Image Classification (HP)
|
100% |
11361
2.11 KIPS |
|
|
Image Classification (Q)
|
97% |
15539
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1585
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16200
262.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21013
340.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8520
9.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
106669
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
205697
241.1 IPS |
|
|
Object Detection (SP)
|
100% |
1800
142.8 IPS |
|
|
Object Detection (HP)
|
100% |
14041
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18994
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3034
36.0 IPS |
|
|
Face Detection (HP)
|
100% |
33469
397.7 IPS |
|
|
Face Detection (Q)
|
100% |
53131
631.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7108
54.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78360
603.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
127529
997.1 IPS |
|
|
Style Transfer (SP)
|
100% |
22037
28.3 IPS |
|
|
Style Transfer (HP)
|
100% |
208016
267.4 IPS |
|
|
Style Transfer (Q)
|
96% |
255462
329.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5075
187.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34031
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
60142
2.22 KIPS |
|
|
Text Classification (SP)
|
100% |
3264
4.36 KIPS |
|
|
Text Classification (HP)
|
100% |
2038
2.72 KIPS |
|
|
Text Classification (Q)
|
93% |
1830
2.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
3182
54.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6432
110.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7483
129.3 IPS |
