MacBook Pro (13-inch, 2022)
Geekbench ML Score
9400
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 11 2025 04:34 PM |
| Views | 2 |
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 | 3.45 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% |
3186
596.2 IPS |
|
|
Image Classification (F16)
|
100% |
8912
1.67 KIPS |
|
|
Image Classification (I8)
|
99% |
11554
2.16 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1242
20.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1711
28.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1908
31.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
22925
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
94368
114.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
96378
116.7 IPS |
|
|
Object Detection (F32)
|
100% |
2808
209.6 IPS |
|
|
Object Detection (F16)
|
100% |
5428
405.2 IPS |
|
|
Object Detection (I8)
|
97% |
2866
214.0 IPS |
|
|
Face Detection (F32)
|
100% |
9439
112.2 IPS |
|
|
Face Detection (F16)
|
97% |
20398
242.5 IPS |
|
|
Face Detection (I8)
|
96% |
20402
242.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
16076
124.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
46564
361.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
53588
415.6 IPS |
|
|
Style Transfer (F32)
|
100% |
40698
53.5 IPS |
|
|
Style Transfer (F16)
|
100% |
149479
196.6 IPS |
|
|
Style Transfer (I8)
|
100% |
132548
174.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5970
213.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
32272
1.15 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34319
1.23 KIPS |
|
|
Text Classification (F32)
|
100% |
2118
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3499
5.03 KIPS |
|
|
Text Classification (I8)
|
96% |
3492
5.02 KIPS |
|
|
Machine Translation (F32)
|
0% |
636
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1409
25.9 IPS |
|
|
Machine Translation (I8)
|
0% |
664
12.2 IPS |
