Mac mini (2023)
Geekbench AI Score
9517
Single Precision Score
10386
Half Precision Score
9195
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | September 16 2024 11:24 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B5035e) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5019
933.5 IPS |
|
|
Image Classification (HP)
|
100% |
5132
954.4 IPS |
|
|
Image Classification (Q)
|
97% |
3847
718.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
7238
117.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
7459
120.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
7053
114.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
37180
43.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
39367
45.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
36067
42.3 IPS |
|
|
Object Detection (SP)
|
100% |
4758
377.4 IPS |
|
|
Object Detection (HP)
|
100% |
4931
391.1 IPS |
|
|
Object Detection (Q)
|
91% |
3997
319.4 IPS |
|
|
Face Detection (SP)
|
100% |
16675
198.1 IPS |
|
|
Face Detection (HP)
|
100% |
17439
207.2 IPS |
|
|
Face Detection (Q)
|
100% |
12142
144.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
23920
184.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
24905
191.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
19792
154.7 IPS |
|
|
Style Transfer (SP)
|
100% |
68324
87.8 IPS |
|
|
Style Transfer (HP)
|
100% |
74739
96.1 IPS |
|
|
Style Transfer (Q)
|
96% |
69252
89.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
13208
487.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13781
508.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
10583
390.8 IPS |
|
|
Text Classification (SP)
|
100% |
2260
3.02 KIPS |
|
|
Text Classification (HP)
|
100% |
3847
5.14 KIPS |
|
|
Text Classification (Q)
|
93% |
3816
5.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
1166
20.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1143
19.7 IPS |
|
|
Machine Translation (Q)
|
98% |
1645
28.4 IPS |
