MacBook Pro (13-inch, 2022)
Geekbench ML Score
10061
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 02 2026 07:56 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E5218f) |
| 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% |
3395
635.2 IPS |
|
|
Image Classification (F16)
|
100% |
10514
1.97 KIPS |
|
|
Image Classification (I8)
|
99% |
10389
1.94 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1131
18.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1839
30.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1973
33.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
23015
27.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
92603
112.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
96971
117.4 IPS |
|
|
Object Detection (F32)
|
100% |
2057
153.6 IPS |
|
|
Object Detection (F16)
|
100% |
5481
409.2 IPS |
|
|
Object Detection (I8)
|
97% |
2137
159.5 IPS |
|
|
Face Detection (F32)
|
100% |
9582
113.9 IPS |
|
|
Face Detection (F16)
|
98% |
17551
208.7 IPS |
|
|
Face Detection (I8)
|
97% |
20766
246.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
16157
125.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
50501
391.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
50645
392.7 IPS |
|
|
Style Transfer (F32)
|
100% |
28156
37.0 IPS |
|
|
Style Transfer (F16)
|
100% |
134308
176.7 IPS |
|
|
Style Transfer (I8)
|
100% |
124995
164.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8396
299.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33719
1.20 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36056
1.29 KIPS |
|
|
Text Classification (F32)
|
100% |
3800
5.46 KIPS |
|
|
Text Classification (F16)
|
100% |
5871
8.44 KIPS |
|
|
Text Classification (I8)
|
96% |
5534
7.95 KIPS |
|
|
Machine Translation (F32)
|
100% |
1233
22.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1396
25.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1072
19.7 IPS |
