MacBook Pro (13-inch, 2022)
Geekbench ML Score
8616
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 16 2025 07:08 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D5040f) |
| Model | MacBook Pro (13-inch, 2022) |
| Model ID | Mac14,7 |
| Motherboard | Mac14,7 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.45 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2028
379.4 IPS |
|
|
Image Classification (F16)
|
100% |
11015
2.06 KIPS |
|
|
Image Classification (I8)
|
99% |
11712
2.19 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1334
22.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1973
33.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1281
21.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
16186
19.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
95037
115.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
97464
118.0 IPS |
|
|
Object Detection (F32)
|
100% |
2856
213.3 IPS |
|
|
Object Detection (F16)
|
100% |
4733
353.4 IPS |
|
|
Object Detection (I8)
|
97% |
1518
113.3 IPS |
|
|
Face Detection (F32)
|
100% |
6675
79.4 IPS |
|
|
Face Detection (F16)
|
97% |
18865
224.3 IPS |
|
|
Face Detection (I8)
|
96% |
19638
233.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
14049
108.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
57046
442.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
48843
378.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40769
53.6 IPS |
|
|
Style Transfer (F16)
|
100% |
148579
195.4 IPS |
|
|
Style Transfer (I8)
|
100% |
144919
190.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7414
264.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34735
1.24 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33961
1.21 KIPS |
|
|
Text Classification (F32)
|
100% |
1940
2.79 KIPS |
|
|
Text Classification (F16)
|
100% |
3190
4.59 KIPS |
|
|
Text Classification (I8)
|
96% |
2898
4.17 KIPS |
|
|
Machine Translation (F32)
|
100% |
581
10.7 IPS |
|
|
Machine Translation (F16)
|
100% |
934
17.2 IPS |
|
|
Machine Translation (I8)
|
99% |
585
10.8 IPS |
