MacBook Pro (13-inch, 2022)
Geekbench ML Score
10658
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 05 2026 07:08 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E5223i) |
| 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 | 3.47 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% |
3417
639.5 IPS |
|
|
Image Classification (F16)
|
100% |
10748
2.01 KIPS |
|
|
Image Classification (I8)
|
99% |
12139
2.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1503
25.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1995
33.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
2008
33.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
23168
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
69146
83.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
96638
117.0 IPS |
|
|
Object Detection (F32)
|
100% |
2892
215.9 IPS |
|
|
Object Detection (F16)
|
100% |
5592
417.5 IPS |
|
|
Object Detection (I8)
|
97% |
2148
160.4 IPS |
|
|
Face Detection (F32)
|
100% |
9619
114.4 IPS |
|
|
Face Detection (F16)
|
98% |
20735
246.5 IPS |
|
|
Face Detection (I8)
|
97% |
20785
247.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
16388
127.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
64748
502.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
70983
550.5 IPS |
|
|
Style Transfer (F32)
|
100% |
40750
53.6 IPS |
|
|
Style Transfer (F16)
|
100% |
149276
196.4 IPS |
|
|
Style Transfer (I8)
|
100% |
134726
177.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8425
300.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34967
1.25 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36172
1.29 KIPS |
|
|
Text Classification (F32)
|
100% |
3595
5.17 KIPS |
|
|
Text Classification (F16)
|
100% |
5028
7.23 KIPS |
|
|
Text Classification (I8)
|
96% |
5697
8.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
1110
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1401
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1075
19.8 IPS |
