MacBook Pro (13-inch, 2022)
Geekbench ML Score
9517
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | November 12 2025 06:53 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C5031i) |
| 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% |
3409
637.9 IPS |
|
|
Image Classification (F16)
|
100% |
10541
1.97 KIPS |
|
|
Image Classification (I8)
|
99% |
11436
2.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1569
26.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1871
31.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1390
23.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
23522
28.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
77601
94.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
91279
110.5 IPS |
|
|
Object Detection (F32)
|
100% |
2839
211.9 IPS |
|
|
Object Detection (F16)
|
100% |
5657
422.3 IPS |
|
|
Object Detection (I8)
|
97% |
1993
148.8 IPS |
|
|
Face Detection (F32)
|
100% |
4221
50.2 IPS |
|
|
Face Detection (F16)
|
97% |
20360
242.1 IPS |
|
|
Face Detection (I8)
|
96% |
20285
241.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
16562
128.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
52971
410.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
52153
404.4 IPS |
|
|
Style Transfer (F32)
|
100% |
40546
53.3 IPS |
|
|
Style Transfer (F16)
|
100% |
138923
182.7 IPS |
|
|
Style Transfer (I8)
|
100% |
140213
184.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8158
291.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
36323
1.30 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34275
1.22 KIPS |
|
|
Text Classification (F32)
|
100% |
2048
2.94 KIPS |
|
|
Text Classification (F16)
|
100% |
3521
5.06 KIPS |
|
|
Text Classification (I8)
|
96% |
3453
4.96 KIPS |
|
|
Machine Translation (F32)
|
100% |
1055
19.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1411
26.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1071
19.7 IPS |
