MacBook Pro (13-inch, 2022)
Geekbench ML Score
8927
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 06 2026 07:06 PM |
| Views | 7 |
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 | 3.30 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% |
2037
381.2 IPS |
|
|
Image Classification (F16)
|
100% |
9194
1.72 KIPS |
|
|
Image Classification (I8)
|
99% |
10791
2.02 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1091
18.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1517
25.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1773
29.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
22953
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
94278
114.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
81940
99.2 IPS |
|
|
Object Detection (F32)
|
100% |
2201
164.3 IPS |
|
|
Object Detection (F16)
|
100% |
5731
427.9 IPS |
|
|
Object Detection (I8)
|
97% |
2802
209.2 IPS |
|
|
Face Detection (F32)
|
100% |
9273
110.3 IPS |
|
|
Face Detection (F16)
|
97% |
18953
225.3 IPS |
|
|
Face Detection (I8)
|
96% |
19054
226.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
16153
125.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
51386
398.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
63716
494.1 IPS |
|
|
Style Transfer (F32)
|
100% |
36092
47.5 IPS |
|
|
Style Transfer (F16)
|
100% |
127429
167.6 IPS |
|
|
Style Transfer (I8)
|
100% |
128018
168.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6373
227.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
29466
1.05 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
30151
1.08 KIPS |
|
|
Text Classification (F32)
|
100% |
2022
2.91 KIPS |
|
|
Text Classification (F16)
|
100% |
3356
4.82 KIPS |
|
|
Text Classification (I8)
|
96% |
3047
4.38 KIPS |
|
|
Machine Translation (F32)
|
100% |
737
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1368
25.2 IPS |
|
|
Machine Translation (I8)
|
99% |
728
13.4 IPS |
