MacBook Pro (16-inch Late 2019)
Geekbench AI Score
913
Single Precision Score
678
Half Precision Score
456
Quantized Score
Geekbench AI 1.3.0 for macOS AVX2
Result Information
| User | Chineezze |
| Upload Date | March 19 2025 02:43 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Intel Core i9-9980HK |
| System Information | |
|---|---|
| Operating System | macOS 15.3.2 (Build 24D81) |
| Model | MacBook Pro (16-inch Late 2019) |
| Model ID | MacBookPro16,1 |
| Motherboard | Apple Inc. Mac-E1008331FDC96864 MacBookPro16,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i9-9980HK |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
455
84.7 IPS |
|
|
Image Classification (HP)
|
100% |
342
63.5 IPS |
|
|
Image Classification (Q)
|
96% |
190
35.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
537
8.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
443
7.18 IPS |
|
|
Image Segmentation (Q)
|
99% |
307
4.98 IPS |
|
|
Pose Estimation (SP)
|
100% |
2689
3.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
826
0.96 IPS |
|
|
Pose Estimation (Q)
|
96% |
641
0.75 IPS |
|
|
Object Detection (SP)
|
100% |
472
37.4 IPS |
|
|
Object Detection (HP)
|
100% |
367
29.1 IPS |
|
|
Object Detection (Q)
|
92% |
214
17.1 IPS |
|
|
Face Detection (SP)
|
100% |
1041
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
845
10.0 IPS |
|
|
Face Detection (Q)
|
100% |
345
4.10 IPS |
|
|
Depth Estimation (SP)
|
100% |
1415
10.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1199
9.24 IPS |
|
|
Depth Estimation (Q)
|
85% |
729
5.70 IPS |
|
|
Style Transfer (SP)
|
100% |
3637
4.67 IPS |
|
|
Style Transfer (HP)
|
100% |
3090
3.97 IPS |
|
|
Style Transfer (Q)
|
96% |
2219
2.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1671
61.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
634
23.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
390
14.4 IPS |
|
|
Text Classification (SP)
|
100% |
409
546.5 IPS |
|
|
Text Classification (HP)
|
100% |
400
533.7 IPS |
|
|
Text Classification (Q)
|
93% |
404
542.1 IPS |
|
|
Machine Translation (SP)
|
100% |
358
6.17 IPS |
|
|
Machine Translation (HP)
|
100% |
564
9.72 IPS |
|
|
Machine Translation (Q)
|
98% |
563
9.73 IPS |
