iPhone 15 Pro Max
Geekbench AI Score
3752
Single Precision Score
26222
Half Precision Score
36364
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 04:04 PM |
| Views | 1 |
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% |
1573
292.6 IPS |
|
|
Image Classification (HP)
|
100% |
10837
2.02 KIPS |
|
|
Image Classification (Q)
|
97% |
14058
2.62 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1546
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16462
266.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21191
343.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7374
8.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
104952
122.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
202861
237.8 IPS |
|
|
Object Detection (SP)
|
100% |
1655
131.3 IPS |
|
|
Object Detection (HP)
|
100% |
13355
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
16941
1.35 KIPS |
|
|
Face Detection (SP)
|
100% |
3024
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
34134
405.6 IPS |
|
|
Face Detection (Q)
|
100% |
50697
602.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6575
50.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
77108
594.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
125202
978.9 IPS |
|
|
Style Transfer (SP)
|
100% |
20092
25.8 IPS |
|
|
Style Transfer (HP)
|
100% |
204530
262.9 IPS |
|
|
Style Transfer (Q)
|
96% |
245630
317.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4548
167.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34361
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
63547
2.35 KIPS |
|
|
Text Classification (SP)
|
100% |
3295
4.40 KIPS |
|
|
Text Classification (HP)
|
99% |
5411
7.22 KIPS |
|
|
Text Classification (Q)
|
93% |
5801
7.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
3119
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6143
105.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6872
118.8 IPS |
