Mac mini (2023)
Geekbench ML Score
4767
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 09 2024 10:45 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F5074a) |
| Model | Mac mini (2023) |
| Model ID | Mac14,3 |
| Motherboard | Mac14,3 |
| 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3346
626.1 IPS |
|
|
Image Classification (F16)
|
100% |
3359
628.6 IPS |
|
|
Image Classification (I8)
|
99% |
2997
560.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1400
23.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1488
24.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1451
24.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
22840
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
24512
29.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
24154
29.2 IPS |
|
|
Object Detection (F32)
|
100% |
1903
142.0 IPS |
|
|
Object Detection (F16)
|
100% |
2718
202.9 IPS |
|
|
Object Detection (I8)
|
97% |
1755
131.0 IPS |
|
|
Face Detection (F32)
|
100% |
9282
110.4 IPS |
|
|
Face Detection (F16)
|
98% |
10535
125.3 IPS |
|
|
Face Detection (I8)
|
97% |
9982
118.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
15930
123.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
17092
132.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
15726
122.0 IPS |
|
|
Style Transfer (F32)
|
100% |
39950
52.6 IPS |
|
|
Style Transfer (F16)
|
100% |
46777
61.5 IPS |
|
|
Style Transfer (I8)
|
100% |
46739
61.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7369
263.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7918
282.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7640
272.8 IPS |
|
|
Text Classification (F32)
|
100% |
518
744.4 IPS |
|
|
Text Classification (F16)
|
100% |
526
756.2 IPS |
|
|
Text Classification (I8)
|
96% |
560
804.1 IPS |
|
|
Machine Translation (F32)
|
100% |
896
16.5 IPS |
|
|
Machine Translation (F16)
|
100% |
934
17.2 IPS |
|
|
Machine Translation (I8)
|
99% |
857
15.8 IPS |
