iPhone 15 Pro Max
Geekbench AI Score
4034
Single Precision Score
22837
Half Precision Score
30048
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 02:32 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1713
318.6 IPS |
|
|
Image Classification (HP)
|
100% |
11764
2.19 KIPS |
|
|
Image Classification (Q)
|
97% |
15008
2.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1616
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12873
208.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
16059
260.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8528
9.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
106680
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
204734
240.0 IPS |
|
|
Object Detection (SP)
|
100% |
1833
145.4 IPS |
|
|
Object Detection (HP)
|
100% |
13884
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19324
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3202
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
33297
395.6 IPS |
|
|
Face Detection (Q)
|
100% |
48358
574.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7286
56.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
79813
614.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
131361
1.03 KIPS |
|
|
Style Transfer (SP)
|
100% |
22190
28.5 IPS |
|
|
Style Transfer (HP)
|
100% |
137981
177.4 IPS |
|
|
Style Transfer (Q)
|
96% |
164553
212.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5098
188.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35222
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56291
2.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3212
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
2160
2.88 KIPS |
|
|
Text Classification (Q)
|
93% |
1464
1.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
3113
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6167
106.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7305
126.2 IPS |
