Mac mini (2024)
Geekbench AI Score
8638
Single Precision Score
10697
Half Precision Score
9625
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | jamesneill |
| Upload Date | December 28 2024 12:49 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M4 |
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C101) |
| Model | Mac mini (2024) |
| Model ID | Mac16,10 |
| Motherboard | Mac16,10 |
| CPU Information | |
|---|---|
| Name | Apple M4 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M4 |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4806
893.8 IPS |
|
|
Image Classification (HP)
|
100% |
5172
961.8 IPS |
|
|
Image Classification (Q)
|
97% |
4439
828.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
5003
81.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
7112
115.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
7632
123.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
29918
34.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
32266
37.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
30739
36.0 IPS |
|
|
Object Detection (SP)
|
100% |
5082
403.1 IPS |
|
|
Object Detection (HP)
|
100% |
5555
440.7 IPS |
|
|
Object Detection (Q)
|
91% |
4743
379.0 IPS |
|
|
Face Detection (SP)
|
100% |
12906
153.4 IPS |
|
|
Face Detection (HP)
|
100% |
16803
199.7 IPS |
|
|
Face Detection (Q)
|
100% |
12558
149.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
21742
167.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
24084
185.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
20532
160.5 IPS |
|
|
Style Transfer (SP)
|
100% |
60223
77.4 IPS |
|
|
Style Transfer (HP)
|
100% |
72694
93.4 IPS |
|
|
Style Transfer (Q)
|
96% |
68200
88.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
12627
466.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13764
508.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
11000
406.2 IPS |
|
|
Text Classification (SP)
|
100% |
3010
4.02 KIPS |
|
|
Text Classification (HP)
|
100% |
5540
7.39 KIPS |
|
|
Text Classification (Q)
|
93% |
5494
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
986
17.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1327
22.9 IPS |
|
|
Machine Translation (Q)
|
98% |
1300
22.5 IPS |
