iPhone 16 Pro Max
Geekbench AI Score
4619
Single Precision Score
35084
Half Precision Score
47893
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | February 21 2026 08:49 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.4 |
| 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% |
1962
364.9 IPS |
|
|
Image Classification (HP)
|
100% |
14317
2.66 KIPS |
|
|
Image Classification (Q)
|
97% |
19033
3.55 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1849
30.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
18115
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23985
388.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7022
8.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
151611
176.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
287917
337.5 IPS |
|
|
Object Detection (SP)
|
100% |
2361
187.2 IPS |
|
|
Object Detection (HP)
|
100% |
15732
1.25 KIPS |
|
|
Object Detection (Q)
|
89% |
21329
1.71 KIPS |
|
|
Face Detection (SP)
|
100% |
3832
45.5 IPS |
|
|
Face Detection (HP)
|
100% |
41083
488.2 IPS |
|
|
Face Detection (Q)
|
100% |
61431
729.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7380
56.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
93695
721.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
157971
1.23 KIPS |
|
|
Style Transfer (SP)
|
100% |
19789
25.4 IPS |
|
|
Style Transfer (HP)
|
100% |
245356
315.4 IPS |
|
|
Style Transfer (Q)
|
96% |
293375
378.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4613
170.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50167
1.85 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
76444
2.82 KIPS |
|
|
Text Classification (SP)
|
100% |
7095
9.47 KIPS |
|
|
Text Classification (HP)
|
100% |
10657
14.2 KIPS |
|
|
Text Classification (Q)
|
92% |
10448
14.0 KIPS |
|
|
Machine Translation (SP)
|
100% |
4017
69.2 IPS |
|
|
Machine Translation (HP)
|
100% |
9048
155.9 IPS |
|
|
Machine Translation (Q)
|
98% |
9961
172.1 IPS |
