MacBook Pro (13-inch, 2022)
Geekbench ML Score
9637
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 07 2025 06:44 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B5057f) |
| 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% |
3386
633.5 IPS |
|
|
Image Classification (F16)
|
100% |
10855
2.03 KIPS |
|
|
Image Classification (I8)
|
99% |
11084
2.07 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1604
26.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1708
28.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1842
30.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
23476
28.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
85300
103.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
67230
81.4 IPS |
|
|
Object Detection (F32)
|
100% |
2497
186.4 IPS |
|
|
Object Detection (F16)
|
100% |
4907
366.3 IPS |
|
|
Object Detection (I8)
|
97% |
2857
213.3 IPS |
|
|
Face Detection (F32)
|
100% |
9519
113.2 IPS |
|
|
Face Detection (F16)
|
97% |
16957
201.6 IPS |
|
|
Face Detection (I8)
|
96% |
20533
244.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
16564
128.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
57088
442.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
50992
395.4 IPS |
|
|
Style Transfer (F32)
|
100% |
41086
54.0 IPS |
|
|
Style Transfer (F16)
|
100% |
145173
191.0 IPS |
|
|
Style Transfer (I8)
|
100% |
147787
194.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9963
355.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34968
1.25 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
37408
1.34 KIPS |
|
|
Text Classification (F32)
|
100% |
2078
2.99 KIPS |
|
|
Text Classification (F16)
|
100% |
3521
5.06 KIPS |
|
|
Text Classification (I8)
|
96% |
3390
4.87 KIPS |
|
|
Machine Translation (F32)
|
0% |
724
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1408
25.9 IPS |
|
|
Machine Translation (I8)
|
0% |
734
13.5 IPS |
