iPhone 15 Pro Max
Geekbench AI Score
3641
Single Precision Score
26533
Half Precision Score
36286
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 17 2025 07:25 AM |
| 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% |
1480
275.2 IPS |
|
|
Image Classification (HP)
|
100% |
10745
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15198
2.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1505
24.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16332
264.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
21047
341.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6692
7.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
102867
120.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
202678
237.6 IPS |
|
|
Object Detection (SP)
|
100% |
1623
128.7 IPS |
|
|
Object Detection (HP)
|
100% |
13952
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
17936
1.43 KIPS |
|
|
Face Detection (SP)
|
100% |
3025
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
34131
405.6 IPS |
|
|
Face Detection (Q)
|
100% |
49617
589.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6569
50.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78041
601.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
121526
950.1 IPS |
|
|
Style Transfer (SP)
|
100% |
19550
25.1 IPS |
|
|
Style Transfer (HP)
|
100% |
208487
268.0 IPS |
|
|
Style Transfer (Q)
|
96% |
245385
316.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4389
162.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34608
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58378
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3194
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5584
7.45 KIPS |
|
|
Text Classification (Q)
|
93% |
5582
7.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3115
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6399
110.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7060
122.0 IPS |
