iPhone 15 Pro Max
Geekbench AI Score
3998
Single Precision Score
25227
Half Precision Score
36229
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | June 26 2025 04:05 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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
315.2 IPS |
|
|
Image Classification (HP)
|
100% |
10767
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15975
2.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1593
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16605
269.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
21448
347.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8382
9.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
106310
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
206309
241.8 IPS |
|
|
Object Detection (SP)
|
100% |
1806
143.3 IPS |
|
|
Object Detection (HP)
|
100% |
13952
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18690
1.49 KIPS |
|
|
Face Detection (SP)
|
100% |
3158
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
33647
399.8 IPS |
|
|
Face Detection (Q)
|
100% |
52873
628.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7113
54.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
79466
612.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
129549
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21810
28.0 IPS |
|
|
Style Transfer (HP)
|
100% |
208209
267.7 IPS |
|
|
Style Transfer (Q)
|
96% |
253744
327.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5022
185.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33818
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
63994
2.36 KIPS |
|
|
Text Classification (SP)
|
100% |
3267
4.36 KIPS |
|
|
Text Classification (HP)
|
100% |
3221
4.30 KIPS |
|
|
Text Classification (Q)
|
93% |
3504
4.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
3183
54.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6493
111.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7566
130.8 IPS |
