Mac mini (2023)
Geekbench ML Score
9126
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 06:56 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 8 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4839
905.6 IPS |
|
|
Image Classification (F16)
|
100% |
6870
1.29 KIPS |
|
|
Image Classification (I8)
|
99% |
7757
1.45 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2067
34.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1812
30.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1818
30.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
42056
50.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
80701
97.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
81932
99.2 IPS |
|
|
Object Detection (F32)
|
100% |
3267
243.9 IPS |
|
|
Object Detection (F16)
|
100% |
4297
320.8 IPS |
|
|
Object Detection (I8)
|
97% |
3190
238.1 IPS |
|
|
Face Detection (F32)
|
100% |
14752
175.4 IPS |
|
|
Face Detection (F16)
|
97% |
11077
131.7 IPS |
|
|
Face Detection (I8)
|
96% |
11102
132.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
24984
193.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
34739
269.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
34254
265.6 IPS |
|
|
Style Transfer (F32)
|
100% |
74254
97.7 IPS |
|
|
Style Transfer (F16)
|
100% |
134982
177.6 IPS |
|
|
Style Transfer (I8)
|
100% |
134815
177.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11583
413.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16834
601.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15835
565.5 IPS |
|
|
Text Classification (F32)
|
100% |
819
1.18 KIPS |
|
|
Text Classification (F16)
|
100% |
2775
3.99 KIPS |
|
|
Text Classification (I8)
|
96% |
2740
3.94 KIPS |
|
|
Machine Translation (F32)
|
100% |
982
18.1 IPS |
|
|
Machine Translation (F16)
|
100% |
2357
43.4 IPS |
|
|
Machine Translation (I8)
|
99% |
909
16.7 IPS |
