iPhone 16 Pro Max
Geekbench AI Score
4646
Single Precision Score
33074
Half Precision Score
45822
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 14 2025 12:13 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2078
386.5 IPS |
|
|
Image Classification (HP)
|
100% |
15267
2.84 KIPS |
|
|
Image Classification (Q)
|
97% |
20044
3.74 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1981
32.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18349
297.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
24164
391.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
9251
10.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
152461
177.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
292155
342.4 IPS |
|
|
Object Detection (SP)
|
100% |
2365
187.6 IPS |
|
|
Object Detection (HP)
|
100% |
16343
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22939
1.83 KIPS |
|
|
Face Detection (SP)
|
100% |
3893
46.3 IPS |
|
|
Face Detection (HP)
|
100% |
39791
472.8 IPS |
|
|
Face Detection (Q)
|
100% |
56496
671.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
8267
63.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
95367
734.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
159791
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
20348
26.2 IPS |
|
|
Style Transfer (HP)
|
100% |
246072
316.3 IPS |
|
|
Style Transfer (Q)
|
96% |
303867
392.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5502
203.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51092
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84770
3.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3389
4.52 KIPS |
|
|
Text Classification (HP)
|
100% |
4552
6.08 KIPS |
|
|
Text Classification (Q)
|
93% |
4630
6.21 KIPS |
|
|
Machine Translation (SP)
|
100% |
4266
73.5 IPS |
|
|
Machine Translation (HP)
|
100% |
10333
178.0 IPS |
|
|
Machine Translation (Q)
|
98% |
11677
201.8 IPS |
