MacBook Pro (16-inch, 2023)
Geekbench AI Score
4148
Single Precision Score
6743
Half Precision Score
5339
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 18 2024 08:48 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.67 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1384
257.3 IPS |
|
|
Image Classification (HP)
|
100% |
2282
424.5 IPS |
|
|
Image Classification (Q)
|
96% |
1693
316.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1688
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2596
42.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3005
48.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
12817
15.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
25647
29.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
19063
22.3 IPS |
|
|
Object Detection (SP)
|
100% |
1683
133.5 IPS |
|
|
Object Detection (HP)
|
97% |
2719
216.4 IPS |
|
|
Object Detection (Q)
|
94% |
2026
161.5 IPS |
|
|
Face Detection (SP)
|
100% |
3665
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
5796
68.9 IPS |
|
|
Face Detection (Q)
|
100% |
3506
41.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6208
47.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
12149
93.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
8191
64.0 IPS |
|
|
Style Transfer (SP)
|
100% |
24591
31.6 IPS |
|
|
Style Transfer (HP)
|
100% |
38400
49.4 IPS |
|
|
Style Transfer (Q)
|
96% |
29995
38.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5098
188.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6884
254.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4461
164.7 IPS |
|
|
Text Classification (SP)
|
100% |
2284
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
3957
5.28 KIPS |
|
|
Text Classification (Q)
|
93% |
3942
5.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
4598
79.2 IPS |
|
|
Machine Translation (HP)
|
98% |
6388
110.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6330
109.4 IPS |
