MacBook Pro (16-inch, 2023)
Geekbench AI Score
4074
Single Precision Score
27456
Half Precision Score
30723
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| User | fearlipe |
| Upload Date | October 15 2025 02:45 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 26.0.1 (Build 25A362) |
| 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 | 3.68 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1363
253.5 IPS |
|
|
Image Classification (HP)
|
100% |
14458
2.69 KIPS |
|
|
Image Classification (Q)
|
96% |
18281
3.41 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1683
27.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
20156
326.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24934
404.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
12136
14.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
105779
123.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
104424
122.4 IPS |
|
|
Object Detection (SP)
|
100% |
1634
129.6 IPS |
|
|
Object Detection (HP)
|
99% |
15698
1.25 KIPS |
|
|
Object Detection (Q)
|
91% |
17970
1.44 KIPS |
|
|
Face Detection (SP)
|
100% |
3636
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
36989
439.5 IPS |
|
|
Face Detection (Q)
|
100% |
46883
557.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6037
46.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
88659
683.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
108993
851.7 IPS |
|
|
Style Transfer (SP)
|
100% |
25391
32.6 IPS |
|
|
Style Transfer (HP)
|
100% |
204805
263.3 IPS |
|
|
Style Transfer (Q)
|
96% |
187672
242.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4803
177.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
44111
1.63 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
52146
1.93 KIPS |
|
|
Text Classification (SP)
|
100% |
2396
3.20 KIPS |
|
|
Text Classification (HP)
|
99% |
4113
5.49 KIPS |
|
|
Text Classification (Q)
|
93% |
4050
5.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
4327
74.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4129
71.1 IPS |
|
|
Machine Translation (Q)
|
98% |
4326
74.8 IPS |
