MacBook Pro (13-inch, 2022)
Geekbench ML Score
10192
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 19 2026 08:09 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.5 (Build 25F5053d) |
| 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% |
3340
625.0 IPS |
|
|
Image Classification (F16)
|
100% |
10466
1.96 KIPS |
|
|
Image Classification (I8)
|
99% |
11522
2.16 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1487
24.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1948
32.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1975
33.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
23312
28.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
94391
114.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
95052
115.1 IPS |
|
|
Object Detection (F32)
|
100% |
2681
200.2 IPS |
|
|
Object Detection (F16)
|
100% |
4793
357.8 IPS |
|
|
Object Detection (I8)
|
97% |
1833
136.8 IPS |
|
|
Face Detection (F32)
|
100% |
9733
115.7 IPS |
|
|
Face Detection (F16)
|
98% |
20663
245.7 IPS |
|
|
Face Detection (I8)
|
97% |
19608
233.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
15350
119.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
48209
373.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
52940
410.5 IPS |
|
|
Style Transfer (F32)
|
100% |
39422
51.9 IPS |
|
|
Style Transfer (F16)
|
100% |
123673
162.7 IPS |
|
|
Style Transfer (I8)
|
100% |
124959
164.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9348
333.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33034
1.18 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35772
1.28 KIPS |
|
|
Text Classification (F32)
|
100% |
3587
5.16 KIPS |
|
|
Text Classification (F16)
|
100% |
5628
8.09 KIPS |
|
|
Text Classification (I8)
|
96% |
5225
7.51 KIPS |
|
|
Machine Translation (F32)
|
100% |
1136
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1292
23.8 IPS |
|
|
Machine Translation (I8)
|
99% |
971
17.9 IPS |
