MacBook Pro (13-inch, 2022)
Geekbench ML Score
9412
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 05 2025 05:41 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B5042k) |
| 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 | 3.46 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% |
3144
588.3 IPS |
|
|
Image Classification (F16)
|
100% |
10810
2.02 KIPS |
|
|
Image Classification (I8)
|
99% |
11436
2.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1428
23.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1769
29.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1006
16.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
22938
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
80196
97.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
91814
111.2 IPS |
|
|
Object Detection (F32)
|
100% |
2851
212.8 IPS |
|
|
Object Detection (F16)
|
100% |
5414
404.2 IPS |
|
|
Object Detection (I8)
|
97% |
2709
202.3 IPS |
|
|
Face Detection (F32)
|
100% |
9141
108.7 IPS |
|
|
Face Detection (F16)
|
97% |
18994
225.8 IPS |
|
|
Face Detection (I8)
|
96% |
20432
242.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
15244
118.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
43040
333.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
63742
494.3 IPS |
|
|
Style Transfer (F32)
|
100% |
40907
53.8 IPS |
|
|
Style Transfer (F16)
|
100% |
140649
185.0 IPS |
|
|
Style Transfer (I8)
|
100% |
148575
195.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7300
260.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34679
1.24 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33159
1.18 KIPS |
|
|
Text Classification (F32)
|
100% |
2094
3.01 KIPS |
|
|
Text Classification (F16)
|
100% |
3437
4.94 KIPS |
|
|
Text Classification (I8)
|
96% |
3413
4.91 KIPS |
|
|
Machine Translation (F32)
|
100% |
880
16.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1157
21.3 IPS |
|
|
Machine Translation (I8)
|
99% |
876
16.1 IPS |
