iPhone 11 Pro Max
Geekbench ML Score
1722
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 19 2024 04:03 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 11 Pro Max |
| Model ID | iPhone12,5 |
| Motherboard | D431AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.66 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
277
51.9 IPS |
|
|
Image Classification (F16)
|
100% |
2652
496.2 IPS |
|
|
Image Classification (I8)
|
99% |
2616
489.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
223
3.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
338
5.64 IPS |
|
|
Pose Estimation (F32)
|
100% |
2259
2.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
27073
32.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
25566
31.0 IPS |
|
|
Object Detection (F32)
|
100% |
462
34.5 IPS |
|
|
Object Detection (F16)
|
100% |
1210
90.3 IPS |
|
|
Object Detection (I8)
|
97% |
446
33.3 IPS |
|
|
Face Detection (F32)
|
100% |
2532
30.1 IPS |
|
|
Face Detection (F16)
|
98% |
4776
56.8 IPS |
|
|
Face Detection (I8)
|
97% |
4732
56.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
2480
19.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
20764
161.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
20181
156.5 IPS |
|
|
Style Transfer (F32)
|
100% |
5915
7.78 IPS |
|
|
Style Transfer (F16)
|
100% |
18393
24.2 IPS |
|
|
Style Transfer (I8)
|
100% |
17723
23.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1108
39.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5001
178.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4980
177.8 IPS |
|
|
Text Classification (F32)
|
100% |
230
330.9 IPS |
|
|
Text Classification (F16)
|
100% |
301
432.3 IPS |
|
|
Text Classification (I8)
|
96% |
300
430.7 IPS |
|
|
Machine Translation (F32)
|
100% |
215
3.96 IPS |
|
|
Machine Translation (F16)
|
100% |
210
3.87 IPS |
|
|
Machine Translation (I8)
|
99% |
216
3.98 IPS |
