iPhone 16 Pro Max
Geekbench AI Score
4534
Single Precision Score
33297
Half Precision Score
44953
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | February 14 2026 08:51 AM |
| Views | 5 |
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% |
1995
371.0 IPS |
|
|
Image Classification (HP)
|
100% |
14410
2.68 KIPS |
|
|
Image Classification (Q)
|
97% |
18619
3.47 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1769
28.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18080
293.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
23436
379.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8751
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
150540
175.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
288750
338.4 IPS |
|
|
Object Detection (SP)
|
100% |
2317
183.8 IPS |
|
|
Object Detection (HP)
|
100% |
15955
1.27 KIPS |
|
|
Object Detection (Q)
|
91% |
21833
1.74 KIPS |
|
|
Face Detection (SP)
|
100% |
3605
42.8 IPS |
|
|
Face Detection (HP)
|
100% |
39776
472.6 IPS |
|
|
Face Detection (Q)
|
100% |
53273
633.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
8110
62.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94402
727.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
153989
1.20 KIPS |
|
|
Style Transfer (SP)
|
100% |
21492
27.6 IPS |
|
|
Style Transfer (HP)
|
100% |
244870
314.8 IPS |
|
|
Style Transfer (Q)
|
96% |
294796
380.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5386
198.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51852
1.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80435
2.97 KIPS |
|
|
Text Classification (SP)
|
100% |
3762
5.02 KIPS |
|
|
Text Classification (HP)
|
99% |
6161
8.22 KIPS |
|
|
Text Classification (Q)
|
93% |
6186
8.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
4037
69.5 IPS |
|
|
Machine Translation (HP)
|
100% |
9115
157.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10180
175.9 IPS |
