iPhone 16 Pro Max
Geekbench AI Score
4443
Single Precision Score
33257
Half Precision Score
44553
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | December 14 2025 02:17 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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% |
1999
371.8 IPS |
|
|
Image Classification (HP)
|
100% |
14418
2.68 KIPS |
|
|
Image Classification (Q)
|
97% |
18244
3.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1783
28.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
18120
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23421
379.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8728
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
150224
175.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
288333
337.9 IPS |
|
|
Object Detection (SP)
|
100% |
2306
182.9 IPS |
|
|
Object Detection (HP)
|
100% |
15503
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21229
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3629
43.1 IPS |
|
|
Face Detection (HP)
|
100% |
39840
473.4 IPS |
|
|
Face Detection (Q)
|
100% |
53609
637.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7937
61.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
94194
725.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
148287
1.16 KIPS |
|
|
Style Transfer (SP)
|
100% |
18475
23.7 IPS |
|
|
Style Transfer (HP)
|
100% |
245157
315.2 IPS |
|
|
Style Transfer (Q)
|
96% |
294070
379.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5174
191.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51054
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
77867
2.88 KIPS |
|
|
Text Classification (SP)
|
100% |
3750
5.01 KIPS |
|
|
Text Classification (HP)
|
99% |
6353
8.48 KIPS |
|
|
Text Classification (Q)
|
93% |
6329
8.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
4056
69.9 IPS |
|
|
Machine Translation (HP)
|
100% |
9117
157.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10227
176.7 IPS |
