MacBook Pro (16-inch, 2023)
Geekbench AI Score
4360
Single Precision Score
28841
Half Precision Score
32385
Quantized Score
Geekbench AI 1.7.0 for macOS AArch64
Result Information
| User | Itzamna |
| Upload Date | March 26 2026 10:52 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E246) |
| 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% |
1383
257.3 IPS |
|
|
Image Classification (HP)
|
100% |
14486
2.69 KIPS |
|
|
Image Classification (Q)
|
97% |
16613
3.10 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1696
27.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
20043
324.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
25576
414.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
12064
14.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
105848
123.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
104350
122.3 IPS |
|
|
Object Detection (SP)
|
100% |
1666
132.2 IPS |
|
|
Object Detection (HP)
|
99% |
15605
1.24 KIPS |
|
|
Object Detection (Q)
|
89% |
17717
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3691
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
38034
451.9 IPS |
|
|
Face Detection (Q)
|
100% |
51775
615.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6139
47.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
88332
680.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
109722
858.3 IPS |
|
|
Style Transfer (SP)
|
100% |
25311
32.5 IPS |
|
|
Style Transfer (HP)
|
100% |
205716
264.5 IPS |
|
|
Style Transfer (Q)
|
96% |
188678
243.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4836
178.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
42612
1.57 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
51881
1.92 KIPS |
|
|
Text Classification (SP)
|
99% |
4409
5.89 KIPS |
|
|
Text Classification (HP)
|
99% |
6795
9.07 KIPS |
|
|
Text Classification (Q)
|
93% |
6675
8.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
4311
74.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4150
71.5 IPS |
|
|
Machine Translation (Q)
|
98% |
4352
75.2 IPS |
