iPhone 15 Pro Max
Geekbench AI Score
3874
Single Precision Score
6896
Half Precision Score
5639
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 14 2025 07:57 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1685
313.4 IPS |
|
|
Image Classification (HP)
|
100% |
2994
556.7 IPS |
|
|
Image Classification (Q)
|
96% |
2041
381.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1590
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2410
39.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3027
49.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7926
9.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
16235
18.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
13992
16.4 IPS |
|
|
Object Detection (SP)
|
100% |
1751
138.9 IPS |
|
|
Object Detection (HP)
|
97% |
3302
262.9 IPS |
|
|
Object Detection (Q)
|
94% |
2353
187.5 IPS |
|
|
Face Detection (SP)
|
100% |
3115
37.0 IPS |
|
|
Face Detection (HP)
|
100% |
6656
79.1 IPS |
|
|
Face Detection (Q)
|
100% |
3784
45.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6738
51.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
12857
99.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
8938
69.9 IPS |
|
|
Style Transfer (SP)
|
100% |
20622
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
32676
42.0 IPS |
|
|
Style Transfer (Q)
|
96% |
27644
35.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4615
170.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5811
214.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4393
162.2 IPS |
|
|
Text Classification (SP)
|
100% |
3258
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
5701
7.61 KIPS |
|
|
Text Classification (Q)
|
93% |
5690
7.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
3151
54.3 IPS |
|
|
Machine Translation (HP)
|
98% |
6791
117.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6849
118.4 IPS |
