MacBook Pro (13-inch, 2022)
Geekbench ML Score
9220
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 07 2026 07:29 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D5087f) |
| 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% |
2122
397.2 IPS |
|
|
Image Classification (F16)
|
100% |
10027
1.88 KIPS |
|
|
Image Classification (I8)
|
99% |
11704
2.19 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1346
22.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1951
32.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1254
21.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
22355
27.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
94065
113.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
97007
117.5 IPS |
|
|
Object Detection (F32)
|
100% |
2270
169.5 IPS |
|
|
Object Detection (F16)
|
100% |
4787
357.4 IPS |
|
|
Object Detection (I8)
|
97% |
2796
208.7 IPS |
|
|
Face Detection (F32)
|
100% |
9284
110.4 IPS |
|
|
Face Detection (F16)
|
97% |
19784
235.2 IPS |
|
|
Face Detection (I8)
|
96% |
18329
217.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
15150
117.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
53169
412.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
59092
458.3 IPS |
|
|
Style Transfer (F32)
|
100% |
40424
53.2 IPS |
|
|
Style Transfer (F16)
|
100% |
133311
175.4 IPS |
|
|
Style Transfer (I8)
|
100% |
143079
188.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7415
264.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
30868
1.10 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33698
1.20 KIPS |
|
|
Text Classification (F32)
|
100% |
1714
2.46 KIPS |
|
|
Text Classification (F16)
|
100% |
3221
4.63 KIPS |
|
|
Text Classification (I8)
|
96% |
3383
4.86 KIPS |
|
|
Machine Translation (F32)
|
100% |
805
14.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1379
25.4 IPS |
|
|
Machine Translation (I8)
|
99% |
873
16.1 IPS |
