MacBook Pro (13-inch, 2022)
Geekbench ML Score
8807
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | December 30 2025 05:26 PM |
| Views | 15 |
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 | 3.13 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% |
3004
562.1 IPS |
|
|
Image Classification (F16)
|
100% |
9344
1.75 KIPS |
|
|
Image Classification (I8)
|
99% |
9766
1.83 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1079
18.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1574
26.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1290
21.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
22563
27.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
92494
112.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
69582
84.3 IPS |
|
|
Object Detection (F32)
|
100% |
2713
202.5 IPS |
|
|
Object Detection (F16)
|
100% |
4821
359.9 IPS |
|
|
Object Detection (I8)
|
97% |
2237
167.0 IPS |
|
|
Face Detection (F32)
|
100% |
8956
106.5 IPS |
|
|
Face Detection (F16)
|
97% |
17654
209.9 IPS |
|
|
Face Detection (I8)
|
96% |
16121
191.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16008
124.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
47702
369.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
50086
388.4 IPS |
|
|
Style Transfer (F32)
|
100% |
36428
47.9 IPS |
|
|
Style Transfer (F16)
|
100% |
139712
183.8 IPS |
|
|
Style Transfer (I8)
|
100% |
141482
186.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5933
211.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
30875
1.10 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36046
1.29 KIPS |
|
|
Text Classification (F32)
|
100% |
2095
3.01 KIPS |
|
|
Text Classification (F16)
|
100% |
2472
3.55 KIPS |
|
|
Text Classification (I8)
|
96% |
3491
5.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
870
16.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1343
24.7 IPS |
|
|
Machine Translation (I8)
|
99% |
886
16.3 IPS |
