iPhone 15 Pro Max
Geekbench AI Score
3787
Single Precision Score
26093
Half Precision Score
35991
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 02:04 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1551
288.5 IPS |
|
|
Image Classification (HP)
|
100% |
10969
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
14492
2.70 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1548
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15498
251.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
21079
341.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7406
8.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
105881
123.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
203768
238.8 IPS |
|
|
Object Detection (SP)
|
100% |
1660
131.7 IPS |
|
|
Object Detection (HP)
|
100% |
13386
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
18766
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3080
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
33927
403.1 IPS |
|
|
Face Detection (Q)
|
100% |
50670
602.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6830
52.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78594
605.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
124732
975.2 IPS |
|
|
Style Transfer (SP)
|
100% |
20811
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
205089
263.6 IPS |
|
|
Style Transfer (Q)
|
96% |
248884
321.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4631
171.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34194
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56192
2.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3248
4.34 KIPS |
|
|
Text Classification (HP)
|
99% |
5449
7.27 KIPS |
|
|
Text Classification (Q)
|
93% |
5453
7.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
3124
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5961
102.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6478
111.9 IPS |
