iPhone 15 Pro Max
Geekbench AI Score
3968
Single Precision Score
24740
Half Precision Score
34777
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 24 2025 12:45 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1695
315.3 IPS |
|
|
Image Classification (HP)
|
100% |
10552
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
14903
2.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1591
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
15788
255.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20856
338.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7945
9.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
106652
124.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
203668
238.7 IPS |
|
|
Object Detection (SP)
|
100% |
1792
142.2 IPS |
|
|
Object Detection (HP)
|
100% |
13700
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19149
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3174
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
34849
414.1 IPS |
|
|
Face Detection (Q)
|
100% |
49942
593.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7217
55.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78401
604.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
128283
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21721
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
204422
262.8 IPS |
|
|
Style Transfer (Q)
|
96% |
249300
321.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5128
189.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34155
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57857
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3197
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3040
4.06 KIPS |
|
|
Text Classification (Q)
|
93% |
3214
4.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
3092
53.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6086
104.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7188
124.2 IPS |
