iPhone 15 Pro Max
Geekbench AI Score
3664
Single Precision Score
26422
Half Precision Score
36807
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 16 2025 07:24 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1568
291.5 IPS |
|
|
Image Classification (HP)
|
100% |
10730
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15693
2.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1523
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16410
266.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
21029
340.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6948
8.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
101943
119.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
193491
226.8 IPS |
|
|
Object Detection (SP)
|
100% |
1621
128.6 IPS |
|
|
Object Detection (HP)
|
100% |
13863
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18461
1.48 KIPS |
|
|
Face Detection (SP)
|
100% |
2937
34.9 IPS |
|
|
Face Detection (HP)
|
100% |
34109
405.3 IPS |
|
|
Face Detection (Q)
|
100% |
51140
607.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6613
50.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
77849
599.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
124200
971.0 IPS |
|
|
Style Transfer (SP)
|
100% |
19396
24.9 IPS |
|
|
Style Transfer (HP)
|
100% |
203061
261.0 IPS |
|
|
Style Transfer (Q)
|
96% |
245131
316.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4304
158.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34134
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
61542
2.27 KIPS |
|
|
Text Classification (SP)
|
100% |
3244
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5609
7.49 KIPS |
|
|
Text Classification (Q)
|
93% |
5673
7.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
3083
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6457
111.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7122
123.1 IPS |
