iPhone 16 Pro Max
Geekbench AI Score
4474
Single Precision Score
33115
Half Precision Score
44629
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| Upload Date | February 12 2026 09:03 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2005
372.9 IPS |
|
|
Image Classification (HP)
|
100% |
14332
2.67 KIPS |
|
|
Image Classification (Q)
|
97% |
18608
3.47 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1740
28.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18103
293.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23702
384.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8656
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
148387
173.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
287973
337.5 IPS |
|
|
Object Detection (SP)
|
100% |
2287
181.4 IPS |
|
|
Object Detection (HP)
|
100% |
15482
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21137
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3539
42.1 IPS |
|
|
Face Detection (HP)
|
100% |
39988
475.1 IPS |
|
|
Face Detection (Q)
|
100% |
53520
635.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7941
61.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
95027
732.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
152859
1.20 KIPS |
|
|
Style Transfer (SP)
|
100% |
20823
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
244499
314.3 IPS |
|
|
Style Transfer (Q)
|
96% |
293590
378.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5309
196.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51955
1.92 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78631
2.90 KIPS |
|
|
Text Classification (SP)
|
100% |
3719
4.96 KIPS |
|
|
Text Classification (HP)
|
99% |
6175
8.24 KIPS |
|
|
Text Classification (Q)
|
93% |
6140
8.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
4034
69.5 IPS |
|
|
Machine Translation (HP)
|
100% |
8926
153.8 IPS |
|
|
Machine Translation (Q)
|
98% |
10071
174.0 IPS |
