MacBook Pro (13-inch, 2022)
Geekbench ML Score
9695
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | February 09 2026 07:53 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D122) |
| 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 | 3.42 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% |
3544
663.2 IPS |
|
|
Image Classification (F16)
|
100% |
11408
2.13 KIPS |
|
|
Image Classification (I8)
|
99% |
12240
2.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1170
19.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1984
33.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
2000
33.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
23128
28.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
86542
104.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
96809
117.2 IPS |
|
|
Object Detection (F32)
|
100% |
2122
158.4 IPS |
|
|
Object Detection (F16)
|
100% |
5364
400.5 IPS |
|
|
Object Detection (I8)
|
97% |
2856
213.2 IPS |
|
|
Face Detection (F32)
|
100% |
9670
115.0 IPS |
|
|
Face Detection (F16)
|
97% |
15958
189.7 IPS |
|
|
Face Detection (I8)
|
96% |
20431
242.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
15658
121.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
47045
364.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
46280
358.9 IPS |
|
|
Style Transfer (F32)
|
100% |
35611
46.8 IPS |
|
|
Style Transfer (F16)
|
100% |
137222
180.5 IPS |
|
|
Style Transfer (I8)
|
100% |
131950
173.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6944
248.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33000
1.18 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34744
1.24 KIPS |
|
|
Text Classification (F32)
|
100% |
2127
3.06 KIPS |
|
|
Text Classification (F16)
|
100% |
3535
5.08 KIPS |
|
|
Text Classification (I8)
|
96% |
3626
5.21 KIPS |
|
|
Machine Translation (F32)
|
100% |
1257
23.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1310
24.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1104
20.3 IPS |
